GitHub Copilot vs OpenCode

Agent access

1. ai-native userPoint an agent at llms.txt or agent-oriented docs

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialprobed6/10

   Probes confirm docs.github.com serves an llms.txt file and a .md-formatted docs page, meaning an agent pointed at docs.github.com could consume agent-oriented docs directly; GitHub also documents MCP server usage for structured context. However, there's no evidence Copilot itself is documented to consume llms.txt as part of its own context-gathering workflow, nor first-party guidance recommending llms.txt for agent use. missing for 10: explicit product documentation instructing users/agents to point Copilot at llms.txt, and independent confirmation this integration is actually used in practice.

   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.github.com/llms.txt # GitHub Docs > GitHub is a developer platform for building, shipping, and mai…”
   • [probe] “PROBE docs-md: HTTP 200 at https://docs.github.com/copilot.md # GitHub Copilot documentation You can use GitHub Copilot to enhance your pro…”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “Learn how to use the GitHub Model Context Protocol (MCP) server to interact with repositories, issues, pull requests, and other GitHub featu…”

   proof ↗⚑ flag

   OpenCode~partialprobed4/10

   OpenCode's own llms.txt file returns 404, so there is no dedicated llms.txt for agents, but probes show that docs pages are available in machine-readable Markdown form (.md suffix returns 200), which serves an analogous agent-oriented documentation function. There's no first-party statement about llms.txt support or explicit agent-doc pointing workflow. Missing for 10: an actual llms.txt endpoint, documentation instructing users to point agents at machine-readable docs, and confirmation that agents can consume the .md docs as intended.

   • [probe] “PROBE llms.txt: HTTP 404 at https://opencode.ai/llms.txt”
   • [probe] “PROBE docs-md: HTTP 200 at https://opencode.ai/docs/.md import { Tabs, TabItem } from "@astrojs/starlight/components" import config from "..…”

   proof ↗⚑ flag

2. ai-native userRun the product headlessly / in CI for automation

   weight 2 · round to OpenCode
   GitHub Copilot~partialprobed7/10

   GitHub Copilot ships a CLI for terminal/headless use and a 'cloud agent' with 'automations' that can run on a schedule or in response to repo events (e.g., issue opened), plus isolated cloud/local sandboxes for execution — all of which enable non-interactive, CI-like automation. However, evidence doesn't show explicit CI pipeline (e.g., GitHub Actions) integration steps or a documented non-interactive/scriptable flag set for true headless scripting. Missing for 10: documented CI/Actions integration examples, explicit non-interactive/headless CLI flags, and independent hands-on confirmation of automation running unattended in CI.

   • [claimed-docs] “The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [probe] “official CLI documented at https://docs.github.com/en/copilot/how-tos/copilot-cli/set-up-copilot-cli/install-copilot-cli”

   proof ↗⚑ flag

   OpenCode✓fullprobed9/10

   OpenCode explicitly supports headless/CI use via `opencode run` for non-interactive execution, `opencode serve` for a headless HTTP server with OpenAPI, `--auto` for unattended permission approval, a JS/TS SDK for programmatic control, and a first-party GitHub Actions integration triggered by PR comments. This covers CLI scripting, server automation, and CI pipelines with concrete docs and an OpenAPI endpoint confirmed live. missing for 10: independent third-party validation of CI reliability at scale (community evidence mostly covers interactive TUI use, not CI-specific automation).

   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “Start OpenCode with --auto to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

3. ai-native userPlug MCP servers into this product so it can use their tools

   weight 3 · round drawn
   GitHub Copilot✓fullclaimed9/10

   GitHub Copilot documents direct MCP server integration: connecting MCP servers to Copilot Chat to extend context/tools, creating custom MCP servers, using the official GitHub MCP server, and admin controls (allow lists) for which MCP servers developers can access. This is well-documented first-party capability across IDE and chat surfaces. missing for 10: independent hands-on community verification of MCP tool usage in practice (community evidence pack is mostly about code suggestion quality/licensing, not MCP specifically).

   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “You can create a new MCP server to fulfill your specific needs, and then integrate it with Copilot Chat.”
   • [claimed-docs] “Learn how to use the GitHub Model Context Protocol (MCP) server to interact with repositories, issues, pull requests, and other GitHub featu…”
   • [claimed-docs] “Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access.”
   • [claimed-docs] “Copilot works where you do—in GitHub, your IDE, the CLI, project tools, chat apps, and custom MCP servers.”

   proof ↗⚑ flag

   OpenCode✓fullclaimed9/10

   OpenCode has first-party documentation dedicated to adding external tools via MCP, supporting both local and remote servers, directly matching the story. This is corroborated indirectly by community discussion of OpenCode's tool/agent ecosystem, though no hands-on account specifically tests MCP server plugging. Missing for 10: independent/hands-on confirmation specifically of MCP server usage (community evidence discusses agents/tools generally but not MCP specifically).

   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP. OpenCode supports both local and remote servers.”
   • [claimed-docs] “You can add external tools to OpenCode using the Model Context Protocol, or MCP.”

   proof ↗⚑ flag

4. ai-native userUse an official CLI

   weight 2 · round to OpenCode
   GitHub Copilot✓fullprobed8/10

   GitHub Copilot ships an official CLI documented at docs.github.com, letting users invoke Copilot directly from the terminal with prompt/voice input, corroborated by a dedicated install guide probe. missing for 10: independent hands-on community review of the CLI itself (community evidence only covers older chat/agent features, not the CLI), and no detail on CLI feature parity with IDE agent mode.

   • [claimed-docs] “The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal.”
   • [claimed-docs] “As an alternative to typing, you can speak your prompt.”
   • [probe] “official CLI documented at https://docs.github.com/en/copilot/how-tos/copilot-cli/set-up-copilot-cli/install-copilot-cli”
   • [claimed-docs] “GitHub Copilot is also supported in terminals through GitHub CLI and as a chat integration in Windows Terminal Canary.”

   proof ↗⚑ flag

   OpenCode✓fullprobed9/10

   OpenCode ships an official CLI with documented commands (opencode run, opencode serve, init, install via curl/npm) and dedicated CLI docs, corroborated by community users who actively use it as their primary daily-driver harness. Missing for 10: independent benchmarking of CLI completeness/stability beyond anecdotal community reports (some bug complaints noted but not disputing existence of an official CLI).

   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP. OpenCode supports both local and remote servers.”
   • [claimed-docs] “curl -fsSL https://opencode.ai/install | bash”
   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “npm install -g opencode-ai”
   • [probe] “official CLI documented at https://opencode.ai/docs/cli/”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”

   proof ↗⚑ flag

5. ai-native userDrive the product through a documented public API

   weight 3 · round to OpenCode
   GitHub Copilot~partialprobed3/10

   GitHub Copilot ships a documented CLI (docs-26, probe-4) that lets scripts/agents invoke Copilot from a terminal, and Copilot Chat can be extended via MCP servers (docs-20/21/25), giving some programmatic hooks. However, an explicit probe for a standard OpenAPI/public API spec returned 404s (probe-3), and no REST/GraphQL API for driving Copilot itself is documented in the evidence. Missing for 10: a dedicated, versioned public API (REST/GraphQL/OpenAPI) for programmatically controlling Copilot beyond CLI/MCP, and independent confirmation of its stability/coverage.

   • [claimed-docs] “The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal.”
   • [probe] “official CLI documented at https://docs.github.com/en/copilot/how-tos/copilot-cli/set-up-copilot-cli/install-copilot-cli”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “You can create a new MCP server to fulfill your specific needs, and then integrate it with Copilot Chat.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.github.com/openapi.json, https://docs.github.com/swagger.json, https://docs.github.com/…”

   proof ↗⚑ flag

   OpenCode✓fullprobed8/10

   OpenCode ships a documented headless server (`opencode serve`) exposing an OpenAPI endpoint, confirmed live via probe (opencode-probe-3), plus a type-safe JS/TS SDK for programmatic control, and its CLI supports non-interactive scripted use (`opencode run`). missing for 10: independent third-party corroboration of SDK/API usage in production, and no evidence of versioning/stability guarantees or broader language SDK support beyond JS/TS.

   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server.”
   • [claimed-docs] “Use it to build integrations and control opencode programmatically.”
   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”
   • [claimed-docs] “Attach a terminal to an already running OpenCode backend server started via `serve` or `web` commands.”

   proof ↗⚑ flag

6. ai-native userIssue scoped/least-privilege API credentials for an agent

   weight 2 · round drawn
   GitHub Copilot~partialclaimed3/10

   Evidence shows governance-adjacent controls like MCP server allow lists and a central control plane with audit logs for managing agents (docs-10, docs-23), but there is no explicit documentation of issuing scoped or least-privilege API credentials/tokens specifically for an agent's actions. Missing for 10: explicit scoped API credential/token issuance mechanism for agents, fine-grained permission scoping documentation, and independent verification that these controls limit agent API access at a credential level rather than just access-list level.

   • [claimed-docs] “Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”
   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”

   proof ↗⚑ flag

   OpenCode~partialclaimed3/10

   OpenCode's permission config lets you restrict which actions (edit, bash, etc.) an agent may auto-run, prompt for, or block, and enterprise SSO integration centralizes access to an internal AI gateway — both are adjacent to least-privilege agent control, but neither is a mechanism for issuing scoped API credentials/keys specifically to an agent. missing for 10: explicit scoped API-key/credential issuance for agents, credential expiry/rotation, per-agent key scoping documentation, independent verification of this capability.

   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “This centralized config can integrate with your SSO provider and ensures all users access only your internal AI gateway.”

   proof ↗⚑ flag

7. ai-native userBuild against official SDKs

   weight 2 · round to OpenCode
   GitHub Copilot~partialclaimed4/10

   Evidence shows extensibility surfaces (MCP server integration, custom agents, partner 'agent apps') that let developers build on top of Copilot, but there is no dedicated official SDK (e.g., language client libraries or API SDK docs) described in the pack. missing for 10: explicit official SDK/client-library docs, code samples for building third-party apps against a Copilot API, independent developer confirmation of SDK usage.

   • [claimed-docs] “Agent apps let you use partner-built agents directly in your workflows on GitHub, powered by your Copilot subscription.”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “You can create a new MCP server to fulfill your specific needs, and then integrate it with Copilot Chat.”
   • [claimed-docs] “Custom agents allow you to tailor Copilot's expertise for specific tasks.”

   proof ↗⚑ flag

   OpenCode✓fullprobed8/10

   OpenCode documents a dedicated JS/TS SDK ('type-safe client for interacting with the server... use it to build integrations and control opencode programmatically') plus a headless server mode (`opencode serve`) exposing an OpenAPI endpoint, confirmed live by probe (openapi.json returns valid schema). This gives AI-native users official, documented programmatic access beyond the CLI/TUI. Missing for 10: independent hands-on developer reports of building against the SDK, and broader multi-language SDK coverage beyond JS/TS.

   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “Use it to build integrations and control opencode programmatically.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server.”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

8. ai-native userSubscribe to events via webhooks

   weight 2 · round drawn
   GitHub Copilot—none0/10

   Evidence shows Copilot 'automations' can be triggered by repository events (e.g., issue opened) [docs-33, docs-15], but this is Copilot reacting to GitHub events, not an API/webhook mechanism for an external AI-native user to subscribe to Copilot's own events. No documentation describes a webhook subscription endpoint or event payload schema for consuming Copilot activity.

   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”

   proof ↗⚑ flag

   OpenCode—none0/10

   Evidence shows OpenCode has a headless server (`opencode serve`) exposing an OpenAPI/HTTP endpoint and an SDK for programmatic control, but there is no mention anywhere of webhook subscriptions or event-push notifications that clients could register for.

   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server.”

   proof ↗⚑ flag

Agentic features

1. ai-native userGet AI-generated insights and suggestions from my data inside the product

   weight 2 · round to GitHub Copilot
   GitHub Copilot✓fullcommunity8/10

   Copilot generates AI insights/suggestions from the user's own code and repository data via code completion, chat with repo/doc context, code review with severity-labeled comments, and Autofix vulnerability suggestions, and can pull context from GitHub issues/PRs/docs via MCP. Community anecdotes (comm-1, comm-6, comm-7) corroborate real productivity gains from these suggestions, though some criticize suggestion quality on edge cases (comm-2, comm-10). Missing for 10: independent benchmark data quantifying insight accuracy/usefulness and no first-party analytics-style 'insights dashboard' beyond code review/Autofix.

   • [claimed-docs] “Scale knowledge and keep teams consistent by creating a shared source of truth that includes context from your docs and repositories.”
   • [claimed-docs] “GitHub Copilot Autofix provides contextual explanations and code suggestions to help developers fix vulnerabilities in code”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “Learn how to use the GitHub Model Context Protocol (MCP) server to interact with repositories, issues, pull requests, and other GitHub featu…”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [community] “I've been using the alpha for the past 2 weeks, and I'm blown away. Copilot guesses the exact code I want about one in ten times... when it …”
   • [community] “I have absolutely loved copilot so far. I especially love how fast it handles indexing complex n-dimensional arrays... I'd estimate a 10% ve…”
   • [community] “Yesterday, Copilot could not write a program with SymPy... Today it uses SymPy as well as it uses NumPy (occasional mistakes, but overall it…”

   proof ↗⚑ flag

   OpenCode✓fullcommunity7/10

   OpenCode's plan/explore agents let users get AI-generated code analysis and suggested changes without modifying the codebase, directly matching the story of AI-generated insights over the user's data (their code) (opencode-docs-7, opencode-docs-60, opencode-docs-61). Community mentions confirm active use of the agent for analysis/harness work (opencode-comm-1, opencode-comm-3). Missing for 10: independent examples of insight quality/output, and no evidence of insights beyond code (e.g., broader data analytics).

   • [claimed-docs] “Use the plan agent to analyze code and review suggestions without making any code changes.”
   • [claimed-docs] “This agent is useful when you want the LLM to analyze code, suggest changes, or create plans without making any actual modifications to your…”
   • [claimed-docs] “A fast, read-only agent for exploring codebases. Cannot modify files.”
   • [community] “I really like how their subagents work, as a bonus I get to choose which model is in which agent.”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”

   proof ↗⚑ flag

2. ai-native userSet up automations that run autonomously in the background

   weight 2 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   GitHub Copilot's cloud agent explicitly supports background automation: docs describe running Copilot 'automatically, on a schedule or in response to events in a repository' and working 'independently in the background to complete tasks, just like a human developer,' with a control plane to track multiple agent sessions. This directly matches the story of autonomous background automations for an AI-native user. Missing for 10: independent/community hands-on validation specifically of the scheduled/event-triggered automation feature (most community evidence is about code completion quality, not the cloud-agent automation flow).

   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”

   proof ↗⚑ flag

   OpenCode~partialcommunity6/10

   OpenCode ships a documented GitHub Actions integration where mentioning /opencode or /oc in a comment triggers it to autonomously work in a new branch and submit a PR, plus a headless `serve` mode and `--auto` permission flag that let it run unattended, supporting background automations. However there's no dedicated scheduling/cron mechanism, and community evidence flags reliability issues (stuck sessions, tool-call failures) that undercut confidence in unattended runs. missing for 10: scheduled/triggered automation beyond GitHub comment mentions, independent evidence of long-running unattended background jobs succeeding reliably.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “This will walk you through installing the GitHub app, creating the workflow, and setting up secrets.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [community] “There are random bugs with loading/restoring state of the session; Model/Provider selection switch across sessions/projects is often annoyin…”
   • [community] “I've been trying various harnesses like Pi, OpenCode, Qwen Code, and Nanocoder. A common problem I keep running into is failed tool calls, r…”

   proof ↗⚑ flag

3. ai-native userDelegate tasks to a built-in AI assistant inside the product

   weight 3 · round drawn
   GitHub Copilot✓fullcommunity9/10

   GitHub Copilot ships extensive built-in agentic capabilities: agent mode in editors, cloud/background agents that plan-explore-execute autonomously, @copilot mentions on PRs, automations, custom agents, and a CLI, all documented first-party. Community evidence corroborates hands-on usage of the assistant delivering real productivity gains, supporting the delegation story. Missing for 10: independent hands-on validation specifically of the newer autonomous cloud-agent/background task delegation (most community evidence predates these agentic features).

   • [claimed-docs] “Edit files in your workspace in agent mode”
   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [community] “I have absolutely loved copilot so far. I especially love how fast it handles indexing complex n-dimensional arrays... I'd estimate a 10% ve…”
   • [community] “Yesterday, Copilot could not write a program with SymPy... Today it uses SymPy as well as it uses NumPy (occasional mistakes, but overall it…”

   proof ↗⚑ flag

   OpenCode✓fullcommunity9/10

   OpenCode's core function is exactly this: an AI coding agent you delegate tasks to via CLI/TUI/IDE/desktop ('opencode run "Explain how closures work..."'), with multiple agent personas (build, plan, explore) and multi-session parallel delegation, richly documented and corroborated by extensive hands-on community use as a daily coding harness. Missing for 10: no independent benchmark of delegation reliability across all model backends (some community reports of failed tool calls/edits with local models).

   • [claimed-docs] “OpenCode is an open source AI coding agent. It's available as a terminal-based interface, desktop app, or IDE extension.”
   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”
   • [claimed-docs] “Multi-session Start multiple agents in parallel on the same project”
   • [claimed-docs] “You can use the **Tab** key to switch between primary agents during a session.”
   • [claimed-docs] “This agent is useful when you want the LLM to analyze code, suggest changes, or create plans without making any actual modifications to your…”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”
   • [community] “Claude is much better in OpenCode then in Claude Code, OpenCode is just better than Claude Code. Claude Code feels like a complete mess to u…”

   proof ↗⚑ flag

4. ai-native userOperate the product with natural-language commands

   weight 2 · round to OpenCode
   GitHub Copilot✓fullcommunity8/10

   GitHub Copilot offers natural-language interaction across chat, agent mode, CLI, and even voice input, letting users direct edits, reviews, and autonomous tasks conversationally (docs-2, docs-22, docs-26, docs-27). Community evidence corroborates real usage of chat/agent workflows, though some report chat availability limited to specific IDEs and mixed quality of autonomous 'fix the bug' style commands. Missing for 10: independent hands-on validation of natural-language command robustness across all surfaces (mobile, terminal) and no rigorous benchmark of command success rate.

   • [claimed-docs] “Edit files in your workspace in agent mode”
   • [claimed-docs] “chat functionality is currently available only in Visual Studio Code, JetBrains, and Visual Studio”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal.”
   • [claimed-docs] “As an alternative to typing, you can speak your prompt.”
   • [community] “The first video in this post is a perfect example of the problems I see in this space. First the programmer asks the AI to nebulously 'fix t…”

   proof ↗⚑ flag

   OpenCode✓fullcommunity9/10

   OpenCode's core interface is natural-language driven: the CLI example `opencode run "Explain how closures work in JavaScript"` and TUI/desktop/IDE modes are all built around conversational prompts to an AI agent that then edits code, opens branches, and submits PRs. Community usage (comm-1, comm-3, comm-4, comm-11) confirms this is how real users operate it day-to-day as their primary coding harness. Missing for 10: no independent benchmark specifically validating breadth of natural-language command coverage beyond docs/anecdotes.

   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [claimed-docs] “OpenCode is an open source AI coding agent. It's available as a terminal-based interface, desktop app, or IDE extension.”
   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”
   • [community] “Claude is much better in OpenCode then in Claude Code, OpenCode is just better than Claude Code. Claude Code feels like a complete mess to u…”

   proof ↗⚑ flag

Api quality

1. ai-native userExplore an interactive API reference with runnable examples

   weight 2 · round to OpenCode
   GitHub Copilot—none0/10

   The evidence pack shows no interactive API reference or runnable-example explorer for GitHub Copilot; a direct probe for OpenAPI/Swagger specs returned 404s on all candidate paths, and docs are plain markdown/text pages rather than an interactive API console.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.github.com/openapi.json, https://docs.github.com/swagger.json, https://docs.github.com/…”
   • [probe] “PROBE llms.txt: HTTP 200 at https://docs.github.com/llms.txt # GitHub Docs > GitHub is a developer platform for building, shipping, and mai…”
   • [probe] “PROBE docs-md: HTTP 200 at https://docs.github.com/copilot.md # GitHub Copilot documentation You can use GitHub Copilot to enhance your pro…”

   proof ↗⚑ flag

   OpenCode~partialprobed3/10

   OpenCode exposes a raw OpenAPI spec via `opencode serve` and openapi.json, and offers an SDK for programmatic use, but there is no evidence of an actual interactive API reference UI (e.g., Swagger/Redoc-style docs) with runnable/try-it examples. Missing for 10: dedicated interactive API explorer page, runnable code examples, independent confirmation of such a UI existing.

   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

2. ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)

   weight 2 · round to OpenCode
   GitHub Copilot—none0/10

   The evidence pack shows explicit probe attempts to find an OpenAPI/machine-readable spec for GitHub Copilot's docs (openapi.json, swagger.json, etc.) all returning 404, and no other citation mentions a downloadable API spec for Copilot. No documentation or community evidence confirms a machine-readable spec exists.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.github.com/openapi.json, https://docs.github.com/swagger.json, https://docs.github.com/…”

   proof ↗⚑ flag

   OpenCode✓fullprobed9/10

   The docs explicitly state that `opencode serve` runs a headless HTTP server exposing an OpenAPI endpoint, and a live probe confirms a downloadable machine-readable OpenAPI spec at https://opencode.ai/openapi.json. This directly satisfies the story of downloading a machine-readable API spec. Missing for 10: independent/community corroboration of using this OpenAPI spec in practice.

   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

3. ai-native userTest against a sandbox environment without touching production data

   weight 1 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed7/10

   GitHub Copilot explicitly documents that its cloud and local agent execution occurs in isolated sandboxes ('Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network resources securely on your local machine or in fully isolated cloud environments'), directly matching the story of testing/agentic work without touching production systems. Missing for 10: independent/hands-on verification of sandbox isolation guarantees, and explicit mention of protecting 'production data' specifically rather than just execution environment isolation.

   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”

   proof ↗⚑ flag

   OpenCode—none0/10

   OpenCode's docs describe permission controls, --auto approval, and external_directory restrictions, but there is no evidence of a dedicated sandbox/staging environment or mechanism to test against non-production data separate from the user's actual working directory/production files. Community reports even flag security gaps in the local server (opencode-comm-18) rather than any sandboxing feature for safe testing.

   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “Use external_directory to allow tool calls that touch paths outside the working directory where OpenCode was started.”
   • [community] “When server is enabled, any web page served from localhost/127.0.0.1 can execute code; any local process can execute code without authentica…”

   proof ↗⚑ flag

4. ai-native userRely on versioned APIs with a documented deprecation policy

   weight 2 · round drawn
   GitHub Copilot—none0/10

   The evidence pack contains no documentation of a versioned API or deprecation policy for GitHub Copilot; the OpenAPI probe explicitly found all candidate spec paths returning 404, and no other citation addresses API versioning/deprecation commitments.

   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.github.com/openapi.json, https://docs.github.com/swagger.json, https://docs.github.com/…”

   proof ↗⚑ flag

   OpenCode—none0/10

   OpenCode does expose programmatic surfaces (the JS/TS SDK, `opencode serve` HTTP server, and an OpenAPI spec at openapi.json), so an API-versioning/deprecation-policy axis is applicable. However, none of the evidence mentions API version numbers, backward-compatibility guarantees, or any documented deprecation policy/process for the SDK or server API.

   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”

   proof ↗⚑ flag

1. ai-native userPerform bulk operations across many items at once

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialclaimed5/10

   Docs show Copilot can run multiple background cloud-agent sessions in parallel, track them from one control page, and trigger automations on repo events/schedules (docs-8, docs-14, docs-15, docs-33), which supports scaling to many tasks, but there's no explicit evidence of a single bulk command/batch operation (e.g., 'review 50 PRs at once' or 'fix all issues matching X') as a discrete feature. Missing for 10: an explicit bulk-action UI/API (e.g., batch PR review, batch issue triage) and independent confirmation that many items can be processed in one invocation rather than via separate parallel agent sessions.

   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”

   proof ↗⚑ flag

   OpenCode~partialclaimed4/10

   OpenCode's CLI (`opencode run`), SDK, and headless `opencode serve` provide programmatic hooks that could be scripted to loop over many files/tasks, and 'multi-session' lets multiple agents run in parallel on a project — but there is no documented first-class 'bulk operation' feature (e.g. batch refactor, mass file edit) or example of applying one command across many items at once. Missing for 10: explicit bulk/batch operation feature, documentation or examples of running the same task across many files/repos, independent evidence of successful large-scale batch use.

   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”
   • [claimed-docs] “Multi-session Start multiple agents in parallel on the same project”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “Use it to build integrations and control opencode programmatically.”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”

   proof ↗⚑ flag

2. ai-native userDefine rules that trigger actions automatically on events

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   GitHub Copilot documents event/schedule-triggered automations for its cloud agent ('run Copilot cloud agent automatically, on a schedule or in response to events in a repository', 'in response to events such as an issue being opened'), plus @mention-triggered PR actions, matching the story's rule-based automatic action pattern. Missing for 10: no independent/hands-on validation of the automation reliability or examples of complex rule chains beyond schedule/issue triggers.

   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”

   proof ↗⚑ flag

   OpenCode~partialclaimed5/10

   OpenCode supports some automatic rule-triggered behavior: GitHub integration lets a PR/issue comment mention (`/opencode` or `/oc`) automatically trigger the agent to execute tasks in a GitHub Actions runner, and the `permission` config lets you define rules for auto-approving, prompting, or blocking specific tool actions. This covers event-triggered automation in a narrow sense, but there's no general-purpose, user-defined event/rule engine (e.g., file-change hooks, cron-like triggers, custom event listeners) described in the docs. Missing for 10: a general automation/hooks system beyond GitHub comment mentions and permission gating, and independent evidence confirming reliability of these triggers in practice.

   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “This will walk you through installing the GitHub app, creating the workflow, and setting up secrets.”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “OpenCode uses the permission config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “For most permissions, you can use an object to apply different actions based on the tool input.”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed7/10

   GitHub Copilot docs explicitly describe 'Automations' that run the cloud agent on a schedule or in response to repository events, allowing recurring/scheduled agent workflows, plus a control page to track multiple scheduled agent sessions. This directly matches the story of scheduling recurring jobs/workflows. Missing for 10: independent/hands-on corroboration of scheduling reliability, and more detail on cron-like configuration options or failure handling.

   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”

   proof ↗⚑ flag

   OpenCode—none0/10

   No evidence of any scheduling, cron-like, or recurring workflow trigger capability; OpenCode's docs cover CLI, agents, MCP, permissions, SDK, GitHub Actions triggers, and server mode but none describe scheduling or recurring automation. missing for 10: any scheduler/cron feature, recurring job configuration, or workflow trigger on a schedule.

   ⚑ flag

4. ai-native userVersion, review, and roll back my automations

   weight 1 · round to GitHub Copilot
   GitHub Copilot~partialclaimed5/10

   Copilot's cloud-agent automations produce PRs that can be reviewed (code review feature, docs-28/29) and tracked via audit logs and a central control plane (docs-23), and since output flows through Git, changes are inherently versioned and revertible via standard PR/commit mechanics. However, there is no direct evidence of a dedicated versioning or rollback mechanism for the automation definitions/schedules themselves (e.g., automation history, revert-to-previous-config). missing for 10: explicit versioning/rollback UI for automation configs, evidence of rolling back an automation run itself (not just its code output), independent confirmation of this workflow in practice.

   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”

   proof ↗⚑ flag

   OpenCode—none0/10

   Evidence covers agent creation, permissions, sessions, and sharing, but there is no documentation or community mention of versioning automations, reviewing change history, or rolling back agent/workflow configurations — session share links are for reference/debugging, not version control or rollback.

   • [claimed-docs] “**Share links** Share a link to any session for reference or to debug”
   • [claimed-docs] “Share links Share a link to any session for reference or to debug”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “This command will guide you through creating a new agent with a custom system prompt and permission configuration.”

   proof ↗⚑ flag

Background execution

1. ai-native userHave a cloud agent build, test, and demo a feature end-to-end for my review

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialclaimed7/10

   Docs describe a genuine cloud agent that works independently in the background (assign tasks, plan/explore/execute), runs in isolated cloud sandboxes to interact with code/tools/filesystem, and produces PRs for review with automated code review and severity-labeled feedback — covering build, execute, and review end-to-end. However, 'testing' and 'demo' are only implied (sandbox execution, PR review) rather than explicitly documented as a testing/demo step, and there is no independent/hands-on corroboration of the cloud agent specifically completing a full feature end-to-end (community evidence predates/doesn't cover the cloud agent feature). Missing for 10: explicit test-running/verification evidence, a documented demo/preview mechanism, and independent hands-on validation of cloud agent outcomes.

   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Access to Cloud agent and code review”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”

   proof ↗⚑ flag

   OpenCode~partialclaimed6/10

   OpenCode's GitHub integration lets it work in a new branch and submit a PR autonomously when mentioned via `/opencode` in GitHub Actions, and its share-links/session feature lets a reviewer inspect the agent's work — together covering 'build' and 'demo for review' in a cloud context. However, there is no explicit documentation of an automated testing step as part of this workflow, and the 'cloud agent' aspect relies on self-hosted GitHub Actions runners rather than a dedicated managed cloud agent service. Missing for 10: explicit test-execution/validation step in the PR workflow, and a first-party fully-hosted cloud agent (not just Actions-runner based) with demo artifacts.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “**Share links** Share a link to any session for reference or to debug”
   • [claimed-docs] “Share links Share a link to any session for reference or to debug”
   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”

   proof ↗⚑ flag

2. developerDelegate longer-running coding tasks to run in the background in an isolated cloud environment

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   Copilot cloud agent is well documented as delegating tasks to run autonomously in an isolated cloud sandbox, working independently in the background like a human developer, with scheduling/automations, a control page to track multiple sessions, and audit logs for governance. missing for 10: independent hands-on community verification of cloud agent reliability/performance (community evidence pack predates cloud agent feature and doesn't corroborate this specific capability).

   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Access to Cloud agent and code review”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”

   proof ↗⚑ flag

   OpenCode~partialclaimed5/10

   OpenCode documents GitHub integration where mentioning /opencode or /oc triggers it to work in a new branch and submit a PR, executing tasks inside the GitHub Actions runner (an isolated cloud environment), which supports background delegation of coding tasks. However, there's no dedicated general-purpose 'cloud agent' product, persistent cloud session management, or evidence of handling arbitrarily long-running tasks outside the GitHub Actions context. missing for 10: a dedicated hosted/cloud sandbox environment independent of GitHub Actions, evidence of long-running task monitoring/resumption in the cloud, and independent hands-on confirmation of this workflow succeeding.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “This will walk you through installing the GitHub app, creating the workflow, and setting up secrets.”

   proof ↗⚑ flag

3. developerConfigure a reproducible cloud environment with the dependencies and setup steps my repository needs

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialclaimed4/10

   Docs mention 'Cloud and local sandboxes provide isolated execution environments' for Copilot cloud agent and background task automation, implying some environment abstraction, but there is no explicit evidence of a mechanism (e.g., a setup-steps config, devcontainer, or dependency manifest) for developers to define reproducible cloud environment setup steps. Missing for 10: explicit documentation of a configuration file/workflow for specifying dependencies/setup steps, independent confirmation of reproducibility across runs.

   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”

   proof ↗⚑ flag

   OpenCode—none0/10

   The evidence shows OpenCode as a terminal/IDE agent with GitHub PR automation and a headless `serve` mode, but nothing describes a mechanism for developers to declare a reproducible cloud environment (base image, dependencies, setup scripts) that the agent provisions before running. Missing for 10: any devcontainer/config-file spec for cloud sandbox provisioning, dependency installation steps, or documented cloud execution environment configuration.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “This centralized config can integrate with your SSO provider and ensures all users access only your internal AI gateway.”

   proof ↗⚑ flag

Parallel agents

1. ai-native userLaunch fleets of autonomous agents that work in parallel on different tasks for hours or days

   weight 2 · round drawn
   GitHub Copilot~partialclaimed6/10

   GitHub Copilot's cloud agent supports background autonomous work, scheduled/event-triggered automations, and a control page to track and manage multiple agent sessions in parallel (docs-8, docs-14, docs-15, docs-31, docs-33), which covers the 'fleets working in parallel' concept. However, evidence doesn't confirm true multi-hour/multi-day persistent autonomous runs at scale or independent hands-on validation of large fleets; most evidence is vendor docs rather than field reports. missing for 10: independent/hands-on confirmation of long-running (hours/days) parallel agent fleets, concrete scale limits or examples of many simultaneous agents, and community verification of duration/reliability at scale.

   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”

   proof ↗⚑ flag

   OpenCode~partialcommunity6/10

   OpenCode documents multi-session support ('Start multiple agents in parallel on the same project'), subagents with per-agent model choice, and GitHub Actions integration where mentioning /opencode lets it execute unattended tasks and open PRs — all pointing toward parallel, semi-autonomous agent operation. However, there is no explicit documentation or evidence of orchestrating large 'fleets' of agents or of sustained autonomous operation over hours/days, and community reports note agents 'randomly stuck, especially for long/nested sessions,' undercutting long-horizon reliability. Missing for 10: dedicated fleet-management/orchestration tooling, explicit hours/days-long autonomous run support, and independent confirmation of stable long-running parallel agent execution.

   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”
   • [claimed-docs] “Multi-session Start multiple agents in parallel on the same project”
   • [community] “I really like how their subagents work, as a bonus I get to choose which model is in which agent.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [community] “There are random bugs with loading/restoring state of the session; Model/Provider selection switch across sessions/projects is often annoyin…”

   proof ↗⚑ flag

2. developerRun several task attempts in parallel and compare results before choosing one

   weight 1 · round to GitHub Copilot
   GitHub Copilot~partialclaimed5/10

   Copilot's cloud/background agents support launching and tracking multiple agent sessions in parallel from a single control page and desktop workspace (docs-8, docs-14, docs-31), which enables running concurrent tasks. However, there's no explicit documentation of running multiple attempts of the *same* task and comparing outputs before selecting one—the evidence describes managing distinct tasks/agents, not competing solutions to a single task. Missing for 10: explicit multi-attempt-per-task workflow, UI for side-by-side comparison of alternative solutions, and any hands-on/community confirmation of this specific parallel-attempt-and-choose pattern.

   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”

   proof ↗⚑ flag

   OpenCode~partialcommunity4/10

   OpenCode documents 'multi-session' support to start multiple agents in parallel on the same project (opencode-docs-17/38) and share links to sessions for reference/debugging (opencode-docs-18/37), which enables running parallel work and inspecting different sessions. However, there is no documented feature for running multiple attempts at the *same* task specifically to compare outcomes and pick a winner (e.g., no diff/compare UI or attempt-ranking workflow), and community threads discuss general session-state bugs rather than this comparison workflow. Missing for 10: explicit same-task multi-attempt spawning, a built-in comparison/diff view across attempts, and evidence of choosing/merging the best result.

   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”
   • [claimed-docs] “Multi-session Start multiple agents in parallel on the same project”
   • [claimed-docs] “**Share links** Share a link to any session for reference or to debug”
   • [claimed-docs] “Share links Share a link to any session for reference or to debug”
   • [community] “You can start a service via 'opencode serve', it can be accessed from anywhere and has great experience on mobile except a few bugs... The W…”

   proof ↗⚑ flag

Scheduled automation

1. ai-native userSet up always-on agents that run on schedules or triggers to maintain and fix my software autonomously

   weight 2 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   GitHub Copilot explicitly documents scheduled/event-triggered cloud agents ('Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository') that work independently in the background, plus a control plane to track/manage multiple agent sessions and sandboxed execution environments. This directly matches the always-on, autonomous, schedule/trigger-driven maintenance story. Missing for 10: independent/hands-on verification of scheduled agent runs actually fixing software autonomously in production, and more detail on trigger types beyond issue-opened examples.

   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”

   proof ↗⚑ flag

   OpenCode—none0/10

   OpenCode documents CLI/TUI/desktop agents, permission automation, GitHub Actions integration triggered by comments, and a headless server/SDK, but there is no evidence of scheduling (cron-like) or event-trigger-based always-on autonomous agents that proactively maintain/fix software without a user or PR-comment invocation. The GitHub integration is triggered by manual mentions, not autonomous scheduled monitoring. Missing for 10: scheduled/cron-based agent runs, event-driven triggers beyond manual mentions, autonomous 'always-on' background maintenance capability.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”

   proof ↗⚑ flag

Code completion

1. developerReceive inline code completions and next-edit suggestions as I type

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullcommunity9/10

   Docs explicitly claim 'unlimited code completion and next edit suggestions' and inline editor functionality (explaining, completing code, proposing edits), and community reports from real usage confirm inline completions work well in practice (e.g., 'Copilot guesses the exact code I want,' 'occasional mistakes but overall it has the right idea'). Missing for 10: no first-party benchmark or independent quantitative study specifically isolating next-edit-suggestion accuracy separate from general completion quality.

   • [claimed-docs] “Unlimited code completion and next edit suggestions”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [community] “I've been using the alpha for the past 2 weeks, and I'm blown away. Copilot guesses the exact code I want about one in ten times... when it …”
   • [community] “Yesterday, Copilot could not write a program with SymPy... Today it uses SymPy as well as it uses NumPy (occasional mistakes, but overall it…”

   proof ↗⚑ flag

   OpenCode—none0/10

   OpenCode is presented as an agent-driven terminal/desktop/IDE-extension tool that responds to explicit prompts, runs agents, and edits files via chat-like sessions — there is no mention of inline ghost-text completions or next-edit suggestions as the developer types. The IDE integration docs describe opening a terminal split and inserting file references, not autocomplete.

   • [claimed-docs] “OpenCode integrates with VS Code, Cursor, or any IDE that supports a terminal. Just run `opencode` in the terminal to get started.”
   • [claimed-docs] “Use Cmd+Esc (Mac) or Ctrl+Esc (Windows/Linux) to open OpenCode in a split terminal view”
   • [claimed-docs] “Use Cmd+Option+K (Mac) or Alt+Ctrl+K (Linux/Windows) to insert file references.”
   • [claimed-docs] “OpenCode is an open source AI coding agent. It's available as a terminal-based interface, desktop app, or IDE extension.”

   proof ↗⚑ flag

Debugging

1. developerDebug issues and troubleshoot using natural-language queries

   weight 2 · round drawn
   GitHub Copilot✓fullclaimed7/10

   Copilot Chat explicitly supports natural-language interaction for explaining concepts, code review with prioritized issue severity, and agent mode for autonomous exploration and fixing—core debugging/troubleshooting workflows (docs-4, docs-22, docs-28, docs-29). Autofix also provides contextual explanations for vulnerabilities (docs-13), reinforcing NL-driven troubleshooting. missing for 10: a dedicated 'debug' feature description, independent hands-on evidence specifically validating debugging accuracy/success (community evidence focuses on completion quality and licensing concerns, not debugging).

   • [claimed-docs] “chat functionality is currently available only in Visual Studio Code, JetBrains, and Visual Studio”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [claimed-docs] “GitHub Copilot Autofix provides contextual explanations and code suggestions to help developers fix vulnerabilities in code”

   proof ↗⚑ flag

   OpenCode✓fullcommunity7/10

   OpenCode is a terminal/IDE-based coding agent that takes natural-language queries (e.g. `opencode run "Explain how closures work..."`), can explore/read codebases via a dedicated read-only agent, and auto-loads LSPs so it can surface diagnostics/errors while chatting, all of which supports NL-driven debugging and troubleshooting; community users confirm using it as a daily 'harness' with good LSP integration for real work. missing for 10: no dedicated 'debug' or troubleshooting workflow docs, and community reports of failed tool calls/unreliable file edits with some models introduce real-world friction.

   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [claimed-docs] “A fast, read-only agent for exploring codebases.”
   • [claimed-docs] “A fast, read-only agent for exploring codebases. Cannot modify files.”
   • [claimed-docs] “LSP enabled Automatically loads the right LSPs for the LLM”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “I've been trying various harnesses like Pi, OpenCode, Qwen Code, and Nanocoder. A common problem I keep running into is failed tool calls, r…”

   proof ↗⚑ flag

Feature implementation

1. developerTurn a tracked issue into a complete pull request end-to-end

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   GitHub Copilot's cloud agent can be assigned directly from an issue or via @copilot mentions, working autonomously to plan, explore, execute changes, and open a pull request, with automations to trigger this on issue events; the desktop workspace lets developers track, review, and merge the resulting PR end-to-end. missing for 10: independent hands-on verification of the full issue-to-merged-PR flow (community evidence covers earlier code-completion/chat era, not cloud agent specifically) and concrete success-rate data on autonomous PR quality.

   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”

   proof ↗⚑ flag

   OpenCode✓fullclaimed7/10

   Docs explicitly state OpenCode can be asked to fix an issue or implement a feature, working in a new branch and submitting a PR with all changes, and it integrates with GitHub Actions via /opencode mentions to run tasks end-to-end. This directly covers issue-to-PR automation, though evidence is vendor-documented only without independent hands-on confirmation of the full issue-to-PR flow succeeding. Missing for 10: independent/community verification of a successful end-to-end issue-to-PR run, and detail on how issue tracking (e.g., linking to GitHub issues specifically) is handled beyond the GitHub Actions integration.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “This will walk you through installing the GitHub app, creating the workflow, and setting up secrets.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”

   proof ↗⚑ flag

2. developerDescribe a feature or bug in plain language and have the agent implement or fix it across multiple files

   weight 3 · round drawn
   GitHub Copilot✓fullcommunity8/10

   Docs describe Copilot agent mode editing files across the workspace, cloud agents that plan/explore/execute tasks autonomously (including from plain-language issue/PR descriptions via @copilot mentions), and code review/autofix capabilities, directly matching the story of describing a feature/bug and having it implemented across multiple files. Community evidence corroborates real usage of the agent for multi-file/complex code tasks, though some hands-on reports note quality limitations on nuanced 'fix the bug' requests. Missing for 10: rigorous independent benchmarking of multi-file correctness and more first-hand accounts specifically of cross-file feature implementation success/failure rates.

   • [claimed-docs] “Edit files in your workspace in agent mode”
   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [community] “The first video in this post is a perfect example of the problems I see in this space. First the programmer asks the AI to nebulously 'fix t…”

   proof ↗⚑ flag

   OpenCode✓fullcommunity8/10

   OpenCode is explicitly a coding agent that takes plain-language instructions and edits code, with docs describing it fixing issues/implementing features and submitting PRs (opencode-docs-12), a CLI for prompting tasks (opencode-docs-22), and permission/auto-approve config for autonomous multi-file changes (opencode-docs-13/14). Community reports corroborate real-world multi-file coding use, with several users calling it their primary harness replacing Aider/Claude Code (opencode-comm-1, opencode-comm-3, opencode-comm-4, opencode-comm-11, opencode-comm-14), though some report unreliable file edits with certain local models and failed tool calls in general (opencode-comm-10, opencode-comm-12). Missing for 10: independent benchmark data on multi-file edit accuracy, and resolution of the reported local-model editing reliability issues.

   • [claimed-docs] “OpenCode is an open source AI coding agent. It's available as a terminal-based interface, desktop app, or IDE extension.”
   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [community] “I really like how their subagents work, as a bonus I get to choose which model is in which agent.”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”
   • [community] “Claude is much better in OpenCode then in Claude Code, OpenCode is just better than Claude Code. Claude Code feels like a complete mess to u…”
   • [community] “OpenCode is awesome. Claude Code is nothing special at all. Last month I switched to just using OpenCode with a Codex $200/mo subscription, …”
   • [community] “I haven't been able to successfully get their CLI to reliably edit files when using local models, anybody else having the same problem?”
   • [community] “I've been trying various harnesses like Pi, OpenCode, Qwen Code, and Nanocoder. A common problem I keep running into is failed tool calls, r…”

   proof ↗⚑ flag

Maintenance automation

1. developerHave the agent write tests, fix lint errors, resolve merge conflicts, and update dependencies for me

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   Copilot's agent mode edits files, validates changes, and can autonomously plan/execute tasks (docs-2,3,22,31), code review with severity-labeled feedback and suggested fixes covers lint/quality issues (docs-28,29), and @copilot on PRs plus cloud agent covers merge conflict resolution and general code changes (docs-32). Dependency updates and explicit test-writing aren't separately documented as named features, so this is inferred from general-purpose agent code editing rather than a dedicated capability. missing for 10: explicit documented examples of writing tests, resolving merge conflicts, and updating dependencies as named use cases, and independent hands-on confirmation of these specific tasks.

   • [claimed-docs] “Edit files in your workspace in agent mode”
   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”

   proof ↗⚑ flag

   OpenCode~partialcommunity6/10

   OpenCode is documented as a general-purpose coding agent that can edit files, run shell commands, and even autonomously fix issues and submit PRs (opencode-docs-12, opencode-docs-58), which implies it can perform tasks like writing tests, fixing lint, resolving conflicts, and updating deps as generic coding actions. However, none of the docs explicitly call out test-writing, lint-fixing, merge-conflict resolution, or dependency updates as named capabilities, and community reports note reliability gaps such as failed tool calls and unreliable file edits especially with local models (opencode-comm-10, opencode-comm-12). Missing for 10: explicit documentation or hands-on evidence of test generation, lint-fix workflows, merge-conflict resolution, and dependency-update automation.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”
   • [community] “I haven't been able to successfully get their CLI to reliably edit files when using local models, anybody else having the same problem?”
   • [community] “I've been trying various harnesses like Pi, OpenCode, Qwen Code, and Nanocoder. A common problem I keep running into is failed tool calls, r…”

   proof ↗⚑ flag

Multimodal generation

1. ai-native userGenerate a working app from a sketch, image, or PDF design

   weight 2 · round drawn
   GitHub Copilot—none0/10

   No evidence that Copilot can take a sketch, image, or PDF design and generate a working app from it; documentation focuses on code completion, chat, agent mode, cloud agents, and MCP integration, with no mention of image/PDF-to-code or multimodal design-to-app generation.

   ⚑ flag

   OpenCode—none0/10

   OpenCode's evidence pack shows a terminal/IDE-based coding agent with text prompts, MCP, agents, and CLI/SDK, but there is no mention anywhere of image, sketch, or PDF design input being converted into a working app — no vision/multimodal input capability is documented.

   ⚑ flag

Codebase mapping

1. developerUnderstand how a codebase fits together to find where to start making changes

   weight 3 · round to OpenCode
   GitHub Copilot~partialclaimed5/10

   Copilot Chat in the editor is documented to explain concepts and provide context-aware help (docs-22), and enterprise features let teams build a 'shared source of truth' from docs and repos (docs-9) plus MCP integrations that pull in repo/issue/PR context (docs-20, docs-21, docs-25), all of which support exploring an unfamiliar codebase. However, there is no explicit feature description of codebase-wide indexing, dependency/architecture mapping, or a dedicated 'explain this repo' capability, and no hands-on community evidence confirming it helps developers orient in large codebases. Missing for 10: dedicated codebase-mapping/semantic search feature docs, explicit onboarding/architecture-understanding use case, and independent corroboration of effectiveness.

   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “Scale knowledge and keep teams consistent by creating a shared source of truth that includes context from your docs and repositories.”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “You can create a new MCP server to fulfill your specific needs, and then integrate it with Copilot Chat.”
   • [claimed-docs] “Learn how to use the GitHub Model Context Protocol (MCP) server to interact with repositories, issues, pull requests, and other GitHub featu…”

   proof ↗⚑ flag

   OpenCode✓fullcommunity7/10

   OpenCode ships a dedicated read-only 'explore' agent for scanning codebases and a 'plan' agent that analyzes code and proposes changes without modifying files, backed by automatic LSP loading for the right language context and skills that surface repo-specific instructions; community notes call the LSP integration 'great' for understanding code. Missing for 10: no dedicated codebase-mapping/visualization feature, no independent benchmark of comprehension quality, and no first-hand user account describing successful architecture-level onboarding via these agents.

   • [claimed-docs] “A fast, read-only agent for exploring codebases.”
   • [claimed-docs] “A fast, read-only agent for exploring codebases. Cannot modify files.”
   • [claimed-docs] “Use the plan agent to analyze code and review suggestions without making any code changes.”
   • [claimed-docs] “This agent is useful when you want the LLM to analyze code, suggest changes, or create plans without making any actual modifications to your…”
   • [claimed-docs] “LSP enabled Automatically loads the right LSPs for the LLM”
   • [claimed-docs] “Agent skills let OpenCode discover reusable instructions from your repo or home directory. Skills are loaded on-demand via the native `skill…”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”

   proof ↗⚑ flag

2. developerHave the agent map and explain an entire unfamiliar codebase without manually selecting context files

   weight 3 · round to OpenCode
   GitHub Copilot~partialclaimed5/10

   Copilot's agent mode and cloud agent are documented to 'plan, explore, and execute work autonomously' across a repo, and 'skills' let it perform specialized tasks, implying some autonomous codebase exploration without hand-picked files, but there's no explicit doc describing a whole-codebase 'map and explain' capability. missing for 10: dedicated codebase-mapping/explanation feature docs, evidence of automatic whole-repo context gathering without manual file selection, and independent hands-on confirmation of this specific workflow.

   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Scale knowledge and keep teams consistent by creating a shared source of truth that includes context from your docs and repositories.”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”

   proof ↗⚑ flag

   OpenCode~partialcommunity6/10

   OpenCode ships a dedicated read-only 'explore' agent explicitly for exploring codebases and a plan agent for analyzing code without edits, plus automatic LSP loading that gives it broader code awareness without manual file picking. However there's no documented feature for generating a full repo map/summary or explicit 'explain this whole codebase' workflow beyond agent tool use (e.g. grep/glob/read), and no independent hands-on evidence confirming it successfully maps a large unfamiliar codebase end-to-end. Missing for 10: explicit repo-map/codebase-summary feature, hands-on/independent confirmation of whole-codebase explanation without manual context selection.

   • [claimed-docs] “A fast, read-only agent for exploring codebases.”
   • [claimed-docs] “A fast, read-only agent for exploring codebases. Cannot modify files.”
   • [claimed-docs] “This agent is useful when you want the LLM to analyze code, suggest changes, or create plans without making any actual modifications to your…”
   • [claimed-docs] “LSP enabled Automatically loads the right LSPs for the LLM”
   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”

   proof ↗⚑ flag

Context management

1. developerHave the agent build and recall memory automatically across sessions

   weight 2 · round drawn
   GitHub Copilot—none0/10

   The evidence pack describes agent mode, cloud agents, MCP context, and code review, but nothing about persistent memory that is automatically built and recalled across sessions—closest is a static 'shared source of truth' repository doc feature, not agent-built memory.

   • [claimed-docs] “Scale knowledge and keep teams consistent by creating a shared source of truth that includes context from your docs and repositories.”

   proof ↗⚑ flag

   OpenCode—none0/10

   No evidence in the pack describes any persistent memory feature that automatically builds or recalls context/knowledge across separate sessions; docs cover sessions, sharing, agents, MCP, skills, and permissions, but nothing about automatic cross-session memory persistence or recall.

   ⚑ flag

2. developerInclude multiple project directories in a single session for broader context

   weight 2 · round drawn
   GitHub Copilot—none0/10

   The evidence pack describes agent mode, chat, MCP integrations, and cloud agents, but contains no mention of including multiple project directories/folders in a single Copilot session for broader context. Missing for 10: any documentation of multi-root workspace support, cross-directory indexing, or explicit multi-project context sharing in one session.

   ⚑ flag

   OpenCode—none0/10

   The evidence shows a permission flag (`external_directory`) that lets tool calls touch paths outside the working directory, but there is no documentation or community report describing a way to add multiple project directories into a single session for combined context. Multi-session and multi-agent features are about running parallel sessions, not merging directories into one context.

   • [claimed-docs] “Use external_directory to allow tool calls that touch paths outside the working directory where OpenCode was started.”
   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”
   • [claimed-docs] “Multi-session Start multiple agents in parallel on the same project”

   proof ↗⚑ flag

3. developerAdd a project instructions file to set coding standards and conventions the agent follows

   weight 3 · round to OpenCode
   GitHub Copilot~partialclaimed4/10

   Docs mention 'creating a shared source of truth that includes context from your docs and repositories' to keep teams consistent (github-copilot-docs-9), which gestures at instructions/knowledge-context features, but the evidence pack never explicitly describes a project instructions file (e.g., copilot-instructions.md) or how coding standards/conventions are set and enforced. Missing for 10: explicit documentation of an instructions file mechanism, its scope/format, and confirmation the agent follows it during edits/completions.

   • [claimed-docs] “Scale knowledge and keep teams consistent by creating a shared source of truth that includes context from your docs and repositories.”

   proof ↗⚑ flag

   OpenCode~partialclaimed5/10

   OpenCode's docs mention an `opencode init` step to set up a project (docs-21/39/56) and 'Agent skills' that let OpenCode discover reusable instructions from a repo or home directory (docs-8/28), which suggests some mechanism for project-level guidance, but no evidence explicitly describes a dedicated instructions/config file (e.g., AGENTS.md) for coding standards and conventions. Missing for 10: explicit documentation of a project instructions file format, guidance on writing coding-standards content into it, and independent/hands-on confirmation that the agent actually follows such a file.

   • [claimed-docs] “initialize OpenCode for the project by running the following command.”
   • [claimed-docs] “Next, initialize OpenCode for the project by running the following command.”
   • [claimed-docs] “initialize OpenCode for the project by running the following command”
   • [claimed-docs] “Agent skills let OpenCode discover reusable instructions from your repo or home directory. Skills are loaded on-demand via the native `skill…”
   • [claimed-docs] “Agent skills let OpenCode discover reusable instructions from your repo or home directory.”

   proof ↗⚑ flag

Issue diagnosis

1. developerReproduce issues, narrow down root causes, and verify fixes

   weight 3 · round drawn
   GitHub Copilot~partialclaimed5/10

   Copilot's agent mode and chat can propose edits and 'validate files' (docs-22), Autofix explains and suggests fixes for vulnerabilities (docs-13), and code review flags issues with severity (docs-28/29), which together support parts of root-cause analysis and fix verification, but there is no explicit documentation of reproducing bugs, running/debugging tests, or a dedicated root-cause investigation workflow. missing for 10: explicit reproduction-of-issue workflow, test-execution/debugging tooling, and independent hands-on evidence of root-cause narrowing.

   • [claimed-docs] “GitHub Copilot Autofix provides contextual explanations and code suggestions to help developers fix vulnerabilities in code”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”

   proof ↗⚑ flag

   OpenCode~partialcommunity5/10

   OpenCode's general coding-agent capabilities (shell/tool execution, LSP integration, a read-only 'explore' agent, and a 'plan' agent for analysis without changes) imply support for investigating bugs and iterating on fixes, and community feedback confirms strong LSP-based codebase navigation. However, there is no explicit documentation of a reproduce/debug/verify workflow, test running, or root-cause tooling, and community reports cite failed tool calls and agents getting stuck on long sessions, undermining reliability for this exact workflow. Missing for 10: explicit debugging/test-execution documentation, first-party guidance on reproducing bugs or verifying fixes, and independent hands-on confirmation of successful root-cause workflows.

   • [claimed-docs] “A fast, read-only agent for exploring codebases.”
   • [claimed-docs] “This agent is useful when you want the LLM to analyze code, suggest changes, or create plans without making any actual modifications to your…”
   • [claimed-docs] “A fast, read-only agent for exploring codebases. Cannot modify files.”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “I've been trying various harnesses like Pi, OpenCode, Qwen Code, and Nanocoder. A common problem I keep running into is failed tool calls, r…”
   • [community] “There are random bugs with loading/restoring state of the session; Model/Provider selection switch across sessions/projects is often annoyin…”

   proof ↗⚑ flag

Marketplace

1. developerEquip the agent with custom skills to perform specialized tasks

   weight 1 · round to OpenCode
   GitHub Copilot✓fullclaimed6/10

   Docs explicitly describe a 'Skills' feature ('Skills allow Copilot to perform specialized tasks') and 'Custom agents' that let developers tailor Copilot's expertise, plus MCP server extensibility to add custom tools/context. This directly matches the story of equipping the agent with custom skills, though details are thin. Missing for 10: concrete developer walkthrough of creating a skill, independent/hands-on confirmation of using custom skills, and richer documentation depth beyond a single-line description.

   • [claimed-docs] “Skills allow Copilot to perform specialized tasks.”
   • [claimed-docs] “Custom agents allow you to tailor Copilot's expertise for specific tasks.”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “You can create a new MCP server to fulfill your specific needs, and then integrate it with Copilot Chat.”

   proof ↗⚑ flag

   OpenCode✓fullcommunity8/10

   OpenCode has a dedicated 'Agent Skills' feature that lets it discover reusable, on-demand instructions from repo or home directory via a native `skill` tool, directly matching the custom-skills story, and this is corroborated by community praise for its subagents/customizability. Missing for 10: no independent hands-on report specifically testing custom skill authoring/loading, and no detail on skill packaging/sharing ecosystem.

   • [claimed-docs] “Agent skills let OpenCode discover reusable instructions from your repo or home directory. Skills are loaded on-demand via the native `skill…”
   • [claimed-docs] “Agent skills let OpenCode discover reusable instructions from your repo or home directory.”
   • [community] “I really like how their subagents work, as a bonus I get to choose which model is in which agent.”

   proof ↗⚑ flag

2. engineering-leadIntegrate third-party partner-built agent apps into my workflows

   weight 1 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   Docs explicitly describe 'Agent apps' that let partner-built agents be used directly in GitHub workflows powered by Copilot subscription, plus assigning tasks to third-party agents (Claude, OpenAI Codex) and MCP server integration for extending Copilot with external tools. Missing for 10: independent/hands-on verification of partner agent app integrations and detail on governance/setup friction beyond first-party docs.

   • [claimed-docs] “Agent apps let you use partner-built agents directly in your workflows on GitHub, powered by your Copilot subscription.”
   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “You can create a new MCP server to fulfill your specific needs, and then integrate it with Copilot Chat.”
   • [claimed-docs] “Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access.”

   proof ↗⚑ flag

   OpenCode~partialclaimed5/10

   OpenCode supports MCP (local/remote servers) to add external tools, has an SDK/headless server for programmatic integrations, and GitHub Actions integration—these enable connecting third-party agent apps/tools into workflows. However, there's no evidence of a curated partner marketplace or vendor-vetted third-party 'agent apps' ecosystem beyond generic MCP/tool integration. missing for 10: a documented partner/marketplace ecosystem of pre-built third-party agent apps, case studies of integrating named partner agents, and independent verification of such integrations working smoothly.

   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP. OpenCode supports both local and remote servers.”
   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”

   proof ↗⚑ flag

Team knowledge

1. engineering-leadCreate a shared workspace from my docs and repos as a common source of truth for the team

   weight 1 · round to GitHub Copilot
   GitHub Copilot~partialclaimed5/10

   Docs explicitly claim the ability to 'scale knowledge and keep teams consistent by creating a shared source of truth that includes context from your docs and repositories,' directly matching the story, and related enterprise-governance features (control planes, audit logs, MCP allow-lists) support team-wide consistency. However, this is a single vendor-claimed line item with no elaboration on setup, structure, or how it functions as a 'workspace,' and no independent/hands-on evidence corroborates it. Missing for 10: independent verification, concrete workflow/UI details, and community confirmation that teams actually use this as a shared source of truth.

   • [claimed-docs] “Scale knowledge and keep teams consistent by creating a shared source of truth that includes context from your docs and repositories.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”
   • [claimed-docs] “Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access.”

   proof ↗⚑ flag

   OpenCode—none0/10

   OpenCode offers session share links, repo-based 'agent skills', and enterprise SSO/config, but there is no evidence of a dedicated shared workspace feature that ingests both docs and repos into a common, persistent team source of truth — these are separate, ad-hoc mechanisms rather than a unified workspace.

   ⚑ flag

Tool integration

1. developerConnect the agent to workflow tools like Jira, Slack, and Google Drive to extend its context

   weight 3 · round drawn
   GitHub Copilot~partialclaimed5/10

   Copilot supports connecting to external tools via MCP servers (docs-10, docs-20, docs-21, docs-25, docs-35), and states it can create custom MCP servers for specific needs, which theoretically enables Jira/Slack/Google Drive integration. However, no evidence names first-party or documented connectors for Jira, Slack, or Google Drive specifically. missing for 10: named official integrations or docs referencing Jira/Slack/Google Drive, independent confirmation these connectors work in practice.

   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”
   • [claimed-docs] “You can create a new MCP server to fulfill your specific needs, and then integrate it with Copilot Chat.”
   • [claimed-docs] “Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access.”
   • [claimed-docs] “Copilot works where you do—in GitHub, your IDE, the CLI, project tools, chat apps, and custom MCP servers.”

   proof ↗⚑ flag

   OpenCode~partialclaimed5/10

   OpenCode supports MCP for adding external tools (local and remote servers), which is the generic mechanism by which one could connect Jira/Slack/Google Drive-type integrations, but there is no direct first-party or community evidence of specific Jira, Slack, or Google Drive connectors or integrations. missing for 10: named first-party or community-verified MCP servers/integrations for Jira, Slack, or Google Drive specifically, and any evidence of workflow-tool context extension beyond generic MCP support.

   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP. OpenCode supports both local and remote servers.”
   • [claimed-docs] “You can add external tools to OpenCode using the Model Context Protocol, or MCP.”
   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP.”

   proof ↗⚑ flag

2. developerKick off agent tasks directly from GitHub, GitLab, Linear, or Slack

   weight 2 · round drawn
   GitHub Copilot~partialclaimed4/10

   Docs clearly show agent tasks can be kicked off from GitHub itself (mentioning @copilot on a PR, automations triggered by repo events, cloud agent background execution), and Copilot is described as working across 'chat apps' generically, but no evidence specifically documents launching agent tasks from GitLab, Linear, or Slack. Missing for 10: explicit GitLab integration, explicit Linear integration, explicit Slack integration for triggering agent tasks.

   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “Copilot works where you do—in GitHub, your IDE, the CLI, project tools, chat apps, and custom MCP servers.”
   • [claimed-docs] “Agent apps let you use partner-built agents directly in your workflows on GitHub, powered by your Copilot subscription.”

   proof ↗⚑ flag

   OpenCode~partialclaimed4/10

   OpenCode has documented GitHub integration where mentioning /opencode or /oc in a comment triggers tasks in GitHub Actions, including issue-to-PR workflows, but there is no evidence of native GitLab, Linear, or Slack integrations for kicking off agent tasks. missing for 10: GitLab integration, Linear integration, Slack integration, independent hands-on confirmation of the GitHub Actions flow working reliably.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “This will walk you through installing the GitHub app, creating the workflow, and setting up secrets.”

   proof ↗⚑ flag

Cross device continuity

1. developerStart a task on one device and continue it later from another device or browser

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialclaimed7/10

   Copilot's cloud agent and control-plane features (docs-8, docs-14, docs-31-33) let a developer assign a task to an agent from GitHub or an IDE and later check progress or continue via GitHub.com's centralized control page or desktop workspace, which is inherently accessible cross-device/browser. However, this is inferred from the cloud-agent architecture rather than an explicit 'continue from another device' claim, and there's no independent/hands-on confirmation of seamless handoff. Missing for 10: explicit documentation of cross-device session continuation and independent verification that state/context truly persists and is resumable identically on a different machine or browser.

   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”

   proof ↗⚑ flag

   OpenCode~partialcommunity6/10

   OpenCode supports remote/headless usage via `opencode serve` plus a TUI that can connect to a remote backend, share links for sessions, and a WebUI that can connect to multiple backends from anywhere (including mobile), which enables cross-device continuation of a session. However, this requires manual server setup rather than seamless native cloud sync, and community reports note bugs restoring session state and provider/model selection issues across sessions. missing for 10: first-party seamless cross-device sync without self-hosting a server, official mobile app, and clear documentation/evidence of resuming full task state (not just session sharing) across devices.

   • [claimed-docs] “This allows using the TUI with a remote OpenCode backend.”
   • [claimed-docs] “**Share links** Share a link to any session for reference or to debug”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [community] “You can start a service via 'opencode serve', it can be accessed from anywhere and has great experience on mobile except a few bugs... The W…”
   • [community] “There are random bugs with loading/restoring state of the session; Model/Provider selection switch across sessions/projects is often annoyin…”

   proof ↗⚑ flag

Ide integration

1. developerView interactive diffs and share selected code as context from within my JetBrains IDE

   weight 1 · round to GitHub Copilot
   GitHub Copilot~partialclaimed4/10

   Docs confirm Copilot Chat and agent-mode editing are available in JetBrains IDEs (github-copilot-docs-4, github-copilot-docs-24, github-copilot-docs-22), which implies some in-IDE diff/context capability, but no evidence specifically describes an interactive diff viewer or a 'share selected code as context' feature for JetBrains. Missing for 10: explicit documentation of JetBrains-specific interactive diff UI, explicit context-selection workflow, and independent/hands-on confirmation of these JetBrains features.

   • [claimed-docs] “chat functionality is currently available only in Visual Studio Code, JetBrains, and Visual Studio”
   • [claimed-docs] “GitHub Copilot integrates with leading editors, including Visual Studio Code, Visual Studio, JetBrains IDEs, and Neovim, and, unlike other A…”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”

   proof ↗⚑ flag

   OpenCode—none0/10

   Evidence only shows OpenCode integrating with VS Code, Cursor, or 'any IDE that supports a terminal' via keyboard shortcuts for split-terminal view and inserting file references; there is no mention of a JetBrains-specific plugin, interactive diff viewer, or JetBrains context-sharing UI. missing for 10: JetBrains plugin/extension documentation, interactive diff rendering inside JetBrains, JetBrains-specific 'share selected code' mechanism.

   • [claimed-docs] “OpenCode integrates with VS Code, Cursor, or any IDE that supports a terminal. Just run `opencode` in the terminal to get started.”
   • [claimed-docs] “Use Cmd+Esc (Mac) or Ctrl+Esc (Windows/Linux) to open OpenCode in a split terminal view”
   • [claimed-docs] “Use Cmd+Option+K (Mac) or Alt+Ctrl+K (Linux/Windows) to insert file references.”
   • [claimed-docs] “OpenCode integrates with VS Code, Cursor, or any IDE that supports a terminal.”
   • [claimed-docs] “Use `Cmd+Esc` (Mac) or `Ctrl+Esc` (Windows/Linux) to open OpenCode in a split terminal view”
   • [claimed-docs] “Use `Cmd+Option+K` (Mac) or `Alt+Ctrl+K` (Linux/Windows) to insert file references.”

   proof ↗⚑ flag

2. developerChat with the coding assistant directly inside my IDE for contextual help

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullcommunity9/10

   Docs confirm Copilot Chat is built into VS Code, JetBrains, and Visual Studio for contextual in-IDE chat (explaining concepts, proposing edits, agent mode), and community feedback corroborates real usage inside the editor. Missing for 10: independent hands-on report specifically about the chat UX (most community evidence focuses on completions, not chat).

   • [claimed-docs] “chat functionality is currently available only in Visual Studio Code, JetBrains, and Visual Studio”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “GitHub Copilot integrates with leading editors, including Visual Studio Code, Visual Studio, JetBrains IDEs, and Neovim, and, unlike other A…”
   • [community] “I've been using the alpha for the past 2 weeks, and I'm blown away. Copilot guesses the exact code I want about one in ten times... when it …”

   proof ↗⚑ flag

   OpenCode✓fullcommunity8/10

   OpenCode ships an IDE extension and integrates directly in VS Code/Cursor with in-editor shortcuts (split terminal view, file-reference insertion) for contextual chat, and community users confirm using it as their daily coding harness with LSP integration inside editors. Missing for 10: independent hands-on review specifically of the IDE-extension chat UX (most community feedback is TUI/CLI-focused) and no screenshots/deep detail on in-IDE chat UI beyond shortcuts.

   • [claimed-docs] “OpenCode integrates with VS Code, Cursor, or any IDE that supports a terminal. Just run `opencode` in the terminal to get started.”
   • [claimed-docs] “Any editor Available as a terminal interface, desktop app, and IDE extension”
   • [claimed-docs] “Use Cmd+Esc (Mac) or Ctrl+Esc (Windows/Linux) to open OpenCode in a split terminal view”
   • [claimed-docs] “Use Cmd+Option+K (Mac) or Alt+Ctrl+K (Linux/Windows) to insert file references.”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”

   proof ↗⚑ flag

Session management

1. developerReview diffs visually and run multiple sessions side by side in a desktop app

   weight 2 · round to OpenCode
   GitHub Copilot~partialclaimed4/10

   Docs mention a 'desktop workspace' for launching work, tracking multiple agent sessions, and reviewing changes (docs-8, docs-14), and a code-review feature with inline suggested changes (docs-28), suggesting some diff-review and multi-session tracking capability. However, it's unclear whether this 'desktop workspace' is a native desktop app or a web-based GitHub UI, and there's no explicit description of a visual side-by-side diff viewer or dedicated multi-pane session UI as in competing IDE tools. Missing for 10: confirmation of a true native desktop application (not browser-based), explicit visual diff-viewer description, and independent/hands-on evidence of side-by-side session usage.

   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”

   proof ↗⚑ flag

   OpenCode~partialclaimed5/10

   OpenCode has a documented desktop app with tabs (opencode-docs-19) and multi-session support to run multiple agents in parallel (opencode-docs-17/38), plus session share links; existence of the desktop app is also confirmed on GitHub (opencode-gh-1). However, there is no evidence describing a visual diff-review UI in the desktop app specifically — docs focus on TUI/terminal split views and file references rather than a diff viewer. Missing for 10: explicit documentation or screenshots of a visual diff/code-review interface in the desktop app, and independent/hands-on confirmation of side-by-side session usage in that app.

   • [claimed-docs] “Introducing tabs for desktop. Available on macOS, Windows, and Linux.”
   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”
   • [claimed-docs] “Multi-session Start multiple agents in parallel on the same project”
   • [github] “OpenCode is also available as a desktop application.”
   • [claimed-docs] “Any editor Available as a terminal interface, desktop app, and IDE extension”

   proof ↗⚑ flag

2. engineering-leadManage multiple agent-driven coding sessions from one unified workspace

   weight 2 · round drawn
   GitHub Copilot✓fullclaimed8/10

   Docs describe a unified control page/desktop workspace to launch, track, and manage multiple agent sessions (Copilot, Claude, Codex) with progress tracking, review, merge, and governance/audit logs from one control plane, directly matching the story. Missing for 10: independent hands-on validation of the multi-agent dashboard experience and any reported friction managing many concurrent sessions.

   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”

   proof ↗⚑ flag

   OpenCode✓fullcommunity8/10

   OpenCode explicitly supports multi-session workflows ('Start multiple agents in parallel on the same project'), tabs for desktop, share links for sessions, and a headless server that a WebUI can connect to across multiple backends, which community evidence corroborates ('WebUI... can connect to multiple OpenCode backends at once'). This directly matches an engineering-lead managing multiple agent sessions from one unified workspace. Missing for 10: no first-party documentation of team/organization-level oversight (e.g., viewing/managing sessions started by other engineers) and some reported bugs in session state restoration temper reliability.

   • [claimed-docs] “**Multi-session** Start multiple agents in parallel on the same project”
   • [claimed-docs] “Introducing tabs for desktop. Available on macOS, Windows, and Linux.”
   • [claimed-docs] “**Share links** Share a link to any session for reference or to debug”
   • [claimed-docs] “Multi-session Start multiple agents in parallel on the same project”
   • [claimed-docs] “Share links Share a link to any session for reference or to debug”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [community] “You can start a service via 'opencode serve', it can be accessed from anywhere and has great experience on mobile except a few bugs... The W…”
   • [community] “There are random bugs with loading/restoring state of the session; Model/Provider selection switch across sessions/projects is often annoyin…”

   proof ↗⚑ flag

Terminal workflow

1. developerRun a coding agent locally from my terminal

   weight 3 · round to OpenCode
   GitHub Copilot✓fullprobed7/10

   GitHub Copilot CLI is officially documented as letting developers use Copilot directly from the terminal, including voice-to-text prompting, and is confirmed installable per docs and probe evidence. missing for 10: independent hands-on validation of the CLI agent's local execution/quality, and more detail on its autonomous/agentic capabilities (vs. just chat) within the terminal.

   • [claimed-docs] “The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal.”
   • [claimed-docs] “As an alternative to typing, you can speak your prompt.”
   • [probe] “official CLI documented at https://docs.github.com/en/copilot/how-tos/copilot-cli/set-up-copilot-cli/install-copilot-cli”
   • [claimed-docs] “GitHub Copilot is also supported in terminals through GitHub CLI and as a chat integration in Windows Terminal Canary.”

   proof ↗⚑ flag

   OpenCode✓fullprobed9/10

   OpenCode is explicitly a terminal-based coding agent, installable via curl/npm, run with `opencode` command in any terminal, with rich CLI docs and confirmed hands-on community usage as a daily local terminal harness. Missing for 10: no independent benchmark/security audit fully vetting the terminal experience beyond anecdotal reports (some report TUI compatibility bugs on specific setups).

   • [claimed-docs] “OpenCode is an open source AI coding agent. It's available as a terminal-based interface, desktop app, or IDE extension.”
   • [claimed-docs] “OpenCode integrates with VS Code, Cursor, or any IDE that supports a terminal. Just run `opencode` in the terminal to get started.”
   • [claimed-docs] “curl -fsSL https://opencode.ai/install | bash”
   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [claimed-docs] “OpenCode integrates with VS Code, Cursor, or any IDE that supports a terminal.”
   • [probe] “official CLI documented at https://opencode.ai/docs/cli/”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”

   proof ↗⚑ flag

2. developerRun the agent non-interactively in scripts for workflow automation

   weight 2 · round to OpenCode
   GitHub Copilot~partialclaimed5/10

   Copilot CLI (docs-26) lets you invoke Copilot from a terminal, and Copilot cloud agent 'Automations' (docs-15, docs-33) can be triggered on a schedule or repository events, which supports some non-interactive workflow automation. However, there is no direct evidence of a documented headless/non-interactive CLI flag (e.g., a scripted prompt-and-exit mode with exit codes) for running Copilot CLI itself inside arbitrary scripts. missing for 10: explicit CLI non-interactive/scripting mode docs, evidence of exit-code/output-parsing support for pipelines, independent hands-on confirmation of script usage.

   • [claimed-docs] “The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal.”
   • [claimed-docs] “Automations let you run Copilot cloud agent automatically, on a schedule or in response to events in a repository.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”

   proof ↗⚑ flag

   OpenCode✓fullclaimed8/10

   The `opencode run` CLI command explicitly supports non-interactive one-shot execution (e.g. `opencode run "Explain how closures work"`), and `--auto` flag auto-approves permissions for unattended runs, plus `opencode serve` exposes a headless HTTP/OpenAPI server and JS/TS SDK for scripted/programmatic control, all fitting workflow automation. Missing for 10: independent hands-on evidence of non-interactive scripting reliability/CI use, and no dedicated exit-code/output-format docs for pipeline integration.

   • [claimed-docs] “opencode run "Explain how closures work in JavaScript"”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “Start OpenCode with --auto to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “Attach a terminal to an already running OpenCode backend server started via `serve` or `web` commands.”

   proof ↗⚑ flag

1. ai-native userDo everything through the API that I can do in the UI

   weight 2 · round to OpenCode
   GitHub Copilot~partialprobed3/10

   Copilot offers a CLI (docs-26, probe-4) and MCP server integration (docs-25) that give some programmatic access to Copilot/GitHub features, but there is no evidence of a comprehensive public API/OpenAPI spec covering the full range of UI capabilities (chat, agent mode, cloud agent, code review) — the openapi probe returned 404 for all candidate endpoints (probe-3). Missing for 10: a documented REST/GraphQL API exposing chat, agent-mode edits, cloud-agent orchestration, and code review equivalently to the UI, and any independent confirmation that CLI/MCP covers full feature parity.

   • [claimed-docs] “The command-line interface (CLI) for GitHub Copilot allows you to use Copilot directly from your terminal.”
   • [probe] “official CLI documented at https://docs.github.com/en/copilot/how-tos/copilot-cli/set-up-copilot-cli/install-copilot-cli”
   • [claimed-docs] “Learn how to use the GitHub Model Context Protocol (MCP) server to interact with repositories, issues, pull requests, and other GitHub featu…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://docs.github.com/openapi.json, https://docs.github.com/swagger.json, https://docs.github.com/…”

   proof ↗⚑ flag

   OpenCode~partialprobed6/10

   OpenCode ships a headless server (`opencode serve`) exposing a documented OpenAPI spec (confirmed live at openapi.json) plus a JS/TS SDK explicitly for 'building integrations and controlling opencode programmatically,' and the TUI/WebUI can drive a remote backend — community confirms this works day-to-day including from mobile. However, no evidence explicitly enumerates full feature parity (e.g., agent skill management, permission config, enterprise SSO settings) as exposed via the API/SDK, and there's no independent audit confirming 1:1 UI/API parity. missing for 10: explicit parity documentation covering all UI-only features (skills, permission prompts, enterprise SSO), independent verification of full API coverage.

   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [claimed-docs] “Use it to build integrations and control opencode programmatically.”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”
   • [claimed-docs] “This allows using the TUI with a remote OpenCode backend.”
   • [community] “You can start a service via 'opencode serve', it can be accessed from anywhere and has great experience on mobile except a few bugs... The W…”

   proof ↗⚑ flag

2. ai-native userExport all of my data in open formats and leave

   weight 3 · round drawn
   GitHub Copilot—none0/10

   No evidence in the pack describes any data export feature, open-format export, or account data portability mechanism for GitHub Copilot; documentation covers coding, agents, MCP, and models but nothing about exporting user data or leaving the platform with your data intact.

   ⚑ flag

   OpenCode—none0/10

   No evidence describes an explicit data-export feature or open-format portability guarantee for OpenCode; while it is open-source and stores config/sessions locally, there's no documented 'export all my data and leave' capability, and community threads even note telemetry sent to OpenCode's own servers with no way to disable it (opencode-comm-2), undercutting a clean data-portability story.

   • [community] “OpenCode is sending telemetry to their own servers, even when you're using your own locally hosted models. There are no environment variable…”
   • [claimed-docs] “**Share links** Share a link to any session for reference or to debug”
   • [claimed-docs] “Share links Share a link to any session for reference or to debug”

   proof ↗⚑ flag

3. ai-native userRead the product's source under an open license

   weight 2 · round to OpenCode
   GitHub Copilot—none0/10

   GitHub Copilot is closed-source proprietary software; no evidence in the pack shows any open-license source availability, and community discussion instead focuses on training-data/licensing concerns, not the product's own source code being open.

   ⚑ flag

   OpenCode✓fullcommunity7/10

   OpenCode's docs explicitly describe it as "open source" and a public GitHub repo exists (opencode-gh-1), and community members confirm they read and learned from the actual source code (opencode-comm-6), corroborating that the source is genuinely accessible. missing for 10: explicit citation of the license name/type (e.g., MIT/Apache) in the evidence pack, and a first-party statement pointing to the license file itself.

   • [claimed-docs] “OpenCode is an open source AI coding agent. It's available as a terminal-based interface, desktop app, or IDE extension.”
   • [github] “OpenCode is also available as a desktop application.”
   • [community] “OpenCode source code is even more awesome. I have learned so much from the way they have organized tools, agents, settings and prompts. mode…”

   proof ↗⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round to OpenCode
   GitHub Copilot—none0/10

   GitHub Copilot is a proprietary cloud/IDE-integrated service with no evidence of any self-hostable core model, backend, or deployment option; all documented capabilities rely on GitHub's hosted infrastructure and models. Self-hosting is a legitimate axis for AI-native openness comparisons, but nothing in the evidence pack indicates it is possible.

   ⚑ flag

   OpenCode✓fullprobed8/10

   OpenCode is open source and installable via CLI, with a documented `opencode serve` headless HTTP server exposing an OpenAPI endpoint, plus SDK and remote/TUI client support, enabling full self-hosting of the core agent; community evidence confirms real-world self-hosted use ('opencode serve' accessible remotely) though also flags security hardening gaps around the server. missing for 10: independent audit confirming production-grade self-hosted security, and clearer official self-hosting/deployment guide beyond the serve command docs.

   • [claimed-docs] “curl -fsSL https://opencode.ai/install | bash”
   • [claimed-docs] “The opencode serve command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “The `opencode serve` command runs a headless HTTP server that exposes an OpenAPI endpoint that an opencode client can use.”
   • [claimed-docs] “Attach a terminal to an already running OpenCode backend server started via `serve` or `web` commands.”
   • [claimed-docs] “The opencode JS/TS SDK provides a type-safe client for interacting with the server. Use it to build integrations and control opencode progra…”
   • [probe] “PROBE openapi: HTTP 200 at https://opencode.ai/openapi.json — contains "openapi" key”
   • [community] “You can start a service via 'opencode serve', it can be accessed from anywhere and has great experience on mobile except a few bugs... The W…”
   • [community] “When server is enabled, any web page served from localhost/127.0.0.1 can execute code; any local process can execute code without authentica…”

   proof ↗⚑ flag

Authentication

1. developerAuthenticate with an API key instead of an account login

   weight 2 · round to OpenCode
   GitHub Copilot—none0/10

   No evidence in the pack describes API-key authentication as an alternative to account login; Copilot's auth model is tied to GitHub account/subscription (IDE sign-in, CLI, etc.) with no mention of API keys for developer access.

   ⚑ flag

   OpenCode✓fullclaimed8/10

   OpenCode explicitly supports configuring API keys for any LLM provider as an alternative to logging in via account-based options like GitHub Copilot or ChatGPT Plus/Pro, giving developers a direct API-key auth path rather than requiring account login. Missing for 10: independent hands-on confirmation of the API key setup flow itself and details on key storage/security beyond docs claims.

   • [claimed-docs] “With OpenCode you can use any LLM provider by configuring their API keys.”
   • [claimed-docs] “**GitHub Copilot** Log in with GitHub to use your Copilot account”
   • [claimed-docs] “**ChatGPT Plus/Pro** Log in with OpenAI to use your ChatGPT Plus or Pro account”
   • [claimed-docs] “OpenCode Zen is a list of tested and verified models provided by the OpenCode team.”

   proof ↗⚑ flag

2. engineering-leadAuthenticate through an enterprise identity or cloud platform for compliance and scalability

   weight 2 · round to OpenCode
   GitHub Copilot—none0/10

   No evidence in the pack addresses SSO/SAML, enterprise identity providers (e.g., Okta, Azure AD), or cloud platform authentication for Copilot; docs cover agents, MCP, models, and governance features but not identity/authentication for enterprise compliance. Missing for 10: SSO/SAML integration docs, enterprise IdP support (Azure AD/Okta), any mention of authentication/compliance certifications tied to identity federation.

   ⚑ flag

   OpenCode~partialclaimed6/10

   OpenCode has a documented enterprise config that integrates with SSO and enforces a centralized internal AI gateway, directly addressing enterprise identity/compliance needs, and supports login via GitHub Copilot/OpenAI accounts. However, there's no independent corroboration of this enterprise SSO feature in practice, no detail on supported identity providers (SAML/OIDC specifics), and community discussion focuses on telemetry/security concerns rather than confirming enterprise auth workflows. Missing for 10: independent/hands-on validation of SSO integration, details on supported IdPs, and evidence of enterprise customers actually using this for compliance/scalability.

   • [claimed-docs] “This centralized config can integrate with your SSO provider and ensures all users access only your internal AI gateway.”
   • [claimed-docs] “**GitHub Copilot** Log in with GitHub to use your Copilot account”
   • [claimed-docs] “**ChatGPT Plus/Pro** Log in with OpenAI to use your ChatGPT Plus or Pro account”

   proof ↗⚑ flag

3. developerSign in with my existing product subscription plan to use the coding agent

   weight 2 · round to OpenCode
   GitHub Copilot✓fullclaimed7/10

   Docs show that Copilot's cloud/coding agent features (agent mode, cloud agent, agent apps) are powered by and included in a user's existing Copilot subscription, e.g. 'Agent apps let you use partner-built agents directly in your workflows on GitHub, powered by your Copilot subscription' and 'Access to Cloud agent and code review' listed as plan features, meaning no separate sign-up is needed beyond the existing subscription/login. Missing for 10: explicit tier-by-tier sign-in flow documentation and independent user confirmation that no extra account creation is required beyond the existing GitHub/Copilot login.

   • [claimed-docs] “Agent apps let you use partner-built agents directly in your workflows on GitHub, powered by your Copilot subscription.”
   • [claimed-docs] “Access to Cloud agent and code review”
   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”

   proof ↗⚑ flag

   OpenCode✓fullcommunity8/10

   OpenCode docs explicitly support signing in with existing subscriptions—GitHub Copilot and ChatGPT Plus/Pro—rather than requiring separate API keys, and community comments confirm using subscriptions (e.g., Codex $200/mo) inside OpenCode. Missing for 10: independent hands-on verification of the Copilot/ChatGPT login flow itself and broader coverage of other subscription providers beyond these two.

   • [claimed-docs] “**GitHub Copilot** Log in with GitHub to use your Copilot account”
   • [claimed-docs] “**ChatGPT Plus/Pro** Log in with OpenAI to use your ChatGPT Plus or Pro account”
   • [claimed-docs] “GitHub Copilot Log in with GitHub to use your Copilot account”
   • [claimed-docs] “ChatGPT Plus/Pro Log in with OpenAI to use your ChatGPT Plus or Pro account”
   • [community] “OpenCode is awesome. Claude Code is nothing special at all. Last month I switched to just using OpenCode with a Codex $200/mo subscription, …”

   proof ↗⚑ flag

4. developerSign in with a personal account to get free-tier access without managing API keys

   weight 1 · round to OpenCode
   GitHub Copilot—none0/10

   The evidence pack contains no mention of a free tier, personal GitHub account sign-in flow, or API-key-free authentication for Copilot; all docs items describe features (agent mode, MCP, code review) but never address account-based free-tier access or pricing/sign-in mechanics.

   ⚑ flag

   OpenCode✓fullcommunity7/10

   OpenCode's docs explicitly offer 'Log in with GitHub to use your Copilot account' and 'Log in with OpenAI to use your ChatGPT Plus or Pro account,' letting a developer authenticate with an existing personal subscription instead of managing provider API keys, and OpenCode Zen is noted to include a free coding model. Missing for 10: independent/hands-on user reports specifically confirming this login flow (community comments focus on API keys/local models, not the Copilot/ChatGPT login path), and clarity on any usage limits tied to the free tier.

   • [claimed-docs] “**GitHub Copilot** Log in with GitHub to use your Copilot account”
   • [claimed-docs] “**ChatGPT Plus/Pro** Log in with OpenAI to use your ChatGPT Plus or Pro account”
   • [claimed-docs] “GitHub Copilot Log in with GitHub to use your Copilot account”
   • [claimed-docs] “ChatGPT Plus/Pro Log in with OpenAI to use your ChatGPT Plus or Pro account”
   • [community] “OpenCode source code is even more awesome. I have learned so much from the way they have organized tools, agents, settings and prompts. mode…”

   proof ↗⚑ flag

Model choice

1. developerLet the tool automatically pick the best model for each task

   weight 1 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed7/10

   GitHub's own docs explicitly state Copilot can 'Automatically select the best model for each task' (docs-17), alongside supporting claims about multiple models optimized for speed/accuracy/cost (docs-7, docs-30). Missing for 10: independent/hands-on verification that auto-selection actually works well in practice, and details on how/when it triggers vs manual model choice.

   • [claimed-docs] “Automatically select the best model for each task.”
   • [claimed-docs] “Choose from leading LLMs optimized for speed, accuracy, or cost.”
   • [claimed-docs] “GitHub Copilot supports multiple AI models, each with different strengths. Some prioritize speed and cost-efficiency, while others are optim…”

   proof ↗⚑ flag

   OpenCode—none0/10

   Evidence shows OpenCode supports many providers/models and lets users manually assign a model per agent or switch via Tab, but nothing indicates the tool automatically selects the optimal model for a given task — community feedback even confirms model/provider choice is manual and sometimes annoying to manage across sessions.

   • [community] “I really like how their subagents work, as a bonus I get to choose which model is in which agent.”
   • [community] “There are random bugs with loading/restoring state of the session; Model/Provider selection switch across sessions/projects is often annoyin…”
   • [claimed-docs] “You can use the Tab key to switch between primary agents during a session.”
   • [claimed-docs] “75+ LLM providers through Models.dev, including local models”

   proof ↗⚑ flag

2. developerChoose which underlying AI model powers my session from multiple providers

   weight 2 · round to OpenCode
   GitHub Copilot✓fullclaimed8/10

   GitHub's own docs explicitly state Copilot supports multiple AI models from different providers (e.g., Claude, OpenAI Codex) and lets users 'choose from leading LLMs optimized for speed, accuracy, or cost,' with a dedicated supported-models reference page and an auto-select option. This directly matches the story of choosing the underlying model per session. Missing for 10: independent/hands-on community confirmation of the model-picker UI in practice and details on per-session persistence of the choice.

   • [claimed-docs] “Choose from leading LLMs optimized for speed, accuracy, or cost.”
   • [claimed-docs] “GitHub Copilot supports multiple AI models, each with different strengths. Some prioritize speed and cost-efficiency, while others are optim…”
   • [claimed-docs] “Assign tasks to agents like Copilot, Claude by Anthropic, and OpenAI Codex, and let them plan, explore, and execute work autonomously in the…”
   • [claimed-docs] “Automatically select the best model for each task.”

   proof ↗⚑ flag

   OpenCode✓fullcommunity9/10

   OpenCode explicitly supports configuring any LLM provider via API keys, lists 75+ providers through Models.dev including local models, offers a curated OpenCode Zen model list, and supports logging in with GitHub Copilot or ChatGPT Plus/Pro accounts. Community evidence corroborates real-world use with multiple providers (Claude, Gemini, local llama.cpp, Qwen) and per-agent model selection. Missing for 10: some community reports note model/provider switching across sessions can be buggy or annoying, a minor UX caveat.

   • [claimed-docs] “With OpenCode you can use any LLM provider by configuring their API keys.”
   • [claimed-docs] “OpenCode Zen is a list of tested and verified models provided by the OpenCode team.”
   • [claimed-docs] “75+ LLM providers through Models.dev, including local models”
   • [claimed-docs] “Any model 75+ LLM providers through Models.dev, including local models”
   • [claimed-docs] “**GitHub Copilot** Log in with GitHub to use your Copilot account”
   • [claimed-docs] “**ChatGPT Plus/Pro** Log in with OpenAI to use your ChatGPT Plus or Pro account”
   • [community] “I really like how their subagents work, as a bonus I get to choose which model is in which agent.”
   • [community] “i've been using this as my primary harness for llama.cpp models, Claude, and Gemini for a few months now. the LSP integration is great.”
   • [community] “This replaced Aider for me a couple months back. I use it with Qwen 3.5 running locally when my daily limits run out on my other subscriptio…”
   • [community] “There are random bugs with loading/restoring state of the session; Model/Provider selection switch across sessions/projects is often annoyin…”

   proof ↗⚑ flag

1. ai-native userChoose where my data is stored (region/residency)

   weight 2 · round drawn
   GitHub Copilot—none0/10

   No evidence in the pack mentions data residency, region selection, or geographic storage controls for GitHub Copilot; only data-training opt-out is mentioned, which is a different concern.

   ⚑ flag

   OpenCode—none0/10

   No evidence anywhere in the pack of a region/residency selection feature for data storage; OpenCode's docs focus on provider choice, self-hosting, and enterprise SSO, none of which address data residency. In fact, community reports indicate telemetry is always sent to OpenCode's own servers with no way to disable it, further suggesting the user lacks control over where certain data goes.

   • [community] “OpenCode is sending telemetry to their own servers, even when you're using your own locally hosted models. There are no environment variable…”

   proof ↗⚑ flag

2. ai-native userPrevent my data from being used to train AI models

   weight 3 · round to GitHub Copilot
   GitHub Copilot~partialcommunity6/10

   GitHub's docs explicitly state individual subscribers can opt out of having their data used for AI model training at any time (github-copilot-docs-12), directly satisfying the story's core ask. However, the evidence pack lacks detail on how opt-out is enforced, whether it covers all Copilot data flows (e.g., telemetry, code review, agents), and community commentary voices skepticism (not concrete contradiction) about whether enterprise code can truly be excluded. Missing for 10: independent verification that opt-out is honored in practice, clarity on enterprise/org-level data-use guarantees, and details on scope of what 'training' opt-out actually excludes.

   • [claimed-docs] “Individual subscribers can opt out of having their data used for AI model training at any time”
   • [community] “Well, this can impose a serious risk to companies and their cloud strategy based on GitHub. Can these enterprises really make sure that thei…”

   proof ↗⚑ flag

   OpenCode—none0/10

   The evidence pack contains no documentation of any setting, policy, or opt-out mechanism for preventing user data/code from being used to train AI models (OpenCode's docs focus on providers, agents, permissions, IDE integration, etc., none addressing training-data usage). Community evidence actually suggests the opposite direction of concern: telemetry is sent to OpenCode's own servers even with locally-hosted models with no way to disable it, which further undermines confidence that user data is protected from being retained/used.

   • [community] “OpenCode is sending telemetry to their own servers, even when you're using your own locally hosted models. There are no environment variable…”

   proof ↗⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialcommunity5/10

   GitHub Copilot docs confirm individual subscribers can opt out of AI model training data use at any time, giving some control over data usage, but there is no documented self-service mechanism for deleting stored chat/history data or explicit retention period controls. Community commentary also raises unresolved skepticism about enterprise assurances that code won't be used for training. Missing for 10: explicit data-deletion tooling, documented retention windows, and enterprise-level deletion guarantees beyond opt-out.

   • [claimed-docs] “Individual subscribers can opt out of having their data used for AI model training at any time”
   • [community] “Well, this can impose a serious risk to companies and their cloud strategy based on GitHub. Can these enterprises really make sure that thei…”

   proof ↗⚑ flag

   OpenCode—none0/10

   No documentation describes any data retention or deletion controls, and community evidence indicates the opposite: OpenCode sends telemetry to its own servers even with local models, with no environment variables or flags to disable it, suggesting no user-facing data controls exist.

   • [community] “OpenCode is sending telemetry to their own servers, even when you're using your own locally hosted models. There are no environment variable…”

   proof ↗⚑ flag

4. ai-native userOpt out of telemetry and usage tracking

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialcommunity4/10

   Docs confirm individual subscribers can opt out of having their code data used for AI model training, but this is narrower than opting out of telemetry/usage tracking broadly, and no evidence describes a general telemetry opt-out toggle. Community commentary (comm-5) even notes agreeing to 'additional telemetry terms' during a preview with no opt-out mentioned. Missing for 10: explicit telemetry/usage-tracking opt-out setting, documentation distinguishing telemetry from training-data opt-out, and independent confirmation that opting out actually stops telemetry collection.

   • [claimed-docs] “Individual subscribers can opt out of having their data used for AI model training at any time”
   • [community] “Gigantic caveat: 'I agree to these additional telemetry terms as part of the technical preview.'”

   proof ↗⚑ flag

   OpenCode!disputedcontradicted2/10

   OpenCode's docs make no mention of a telemetry opt-out setting, and a community report explicitly states OpenCode sends telemetry to its own servers even with locally hosted models, with no environment variables, flags, or config options to disable it. This is a first-party-vs-hands-on-evidence conflict: no documented opt-out mechanism exists, and independent evidence claims none is available. missing for 10: any official docs describing a telemetry toggle/opt-out, first-party acknowledgment of telemetry collection, and any evidence the reported issue was fixed.

   • [community] “OpenCode is sending telemetry to their own servers, even when you're using your own locally hosted models. There are no environment variable…”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”

   proof ↗⚑ flag

Data governance

1. engineering-leadOpt out of having my code and prompts used for AI model training

   weight 1 · round to GitHub Copilot
   GitHub Copilot~partialcommunity6/10

   Docs explicitly state individual subscribers can opt out of AI model training at any time (github-copilot-docs-12), which covers a developer-level version of this story. However, evidence does not show an org-wide/enterprise admin policy control that an engineering-lead could set organization-wide, and one community comment expresses skepticism about enterprise assurance (not a concrete contradiction). Missing for 10: enterprise/org-level policy documentation, admin-console controls, and independent verification of enforcement.

   • [claimed-docs] “Individual subscribers can opt out of having their data used for AI model training at any time”
   • [community] “Well, this can impose a serious risk to companies and their cloud strategy based on GitHub. Can these enterprises really make sure that thei…”

   proof ↗⚑ flag

   OpenCode—none0/10

   No documentation exists describing a training-data opt-out or data-use policy for prompts/code; in fact community evidence indicates OpenCode sends telemetry to its own servers with no way to disable it, even when using local models, suggesting the opposite of user control over data usage.

   • [community] “OpenCode is sending telemetry to their own servers, even when you're using your own locally hosted models. There are no environment variable…”

   proof ↗⚑ flag

Pr review

1. developerHave the agent stage changes, write commit messages, create branches, and open pull requests

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed7/10

   GitHub Copilot's cloud/background agent is documented to work independently on tasks, make changes on existing PRs via @copilot mentions, and complete work 'just like a human developer,' which in GitHub's workflow model entails committing changes and opening/updating pull requests (docs-31, docs-32, docs-8, docs-14). However, explicit documentation of branch creation and commit-message authorship mechanics is not directly cited, and there is no independent/hands-on verification of the PR-opening workflow. Missing for 10: explicit branch-creation documentation, independent hands-on confirmation of commit/PR flow, and detail on staging-changes granularity.

   • [claimed-docs] “With Copilot cloud agent, GitHub Copilot can work independently in the background to complete tasks, just like a human developer.”
   • [claimed-docs] “Mention `@copilot` in a comment on an existing pull request to ask it to make changes.”
   • [claimed-docs] “Launch work from GitHub, track progress across multiple agents, review changes, and merge completed work—all from one desktop workspace buil…”
   • [claimed-docs] “Use one centralized control page to jump between agent sessions, check progress, and stay in control without losing your place.”
   • [claimed-docs] “Set up an automation to run Copilot automatically, on a schedule or in response to events such as an issue being opened.”

   proof ↗⚑ flag

   OpenCode~partialclaimed6/10

   Docs explicitly describe GitHub integration where OpenCode 'will work in a new branch and submits a PR with all the changes' and can execute tasks via mentions in GitHub Actions, covering branch creation and PR opening; permission config also governs whether actions like git operations auto-run or prompt. However, there's no explicit mention of staging changes or generating commit messages as a distinct capability, and no independent/community evidence corroborates the PR-creation workflow in practice. missing for 10: explicit documentation of commit message generation/staging step, independent hands-on verification of the branch+PR workflow.

   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “This will walk you through installing the GitHub app, creating the workflow, and setting up secrets.”

   proof ↗⚑ flag

2. developerGet automatic code review with contextual feedback on every pull request

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed7/10

   GitHub Copilot's docs explicitly describe automated PR code review with contextual feedback, suggested fixes, and severity labeling (High/Medium/Low) for prioritization, plus 'Access to Cloud agent and code review' as a plan feature. This directly matches the story's request for automatic, contextual PR review feedback. Missing for 10: independent/hands-on community evidence specifically validating the PR-review feature's accuracy or usefulness (community citations mostly discuss code completion, not the review feature) and detail on review-triggering automation reliability.

   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [claimed-docs] “Access to Cloud agent and code review”

   proof ↗⚑ flag

   OpenCode~partialclaimed4/10

   OpenCode has a GitHub Actions integration (mention /opencode or /oc in a comment) and a read-only 'plan' agent that can review/suggest changes without modifying code, which can be used for PR feedback, but this requires an explicit manual mention rather than automatically triggering contextual review on every PR. Missing for 10: documented automatic/triggerless review on every new PR, evidence of inline contextual comments on diffs, and independent confirmation of this review workflow in practice.

   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”
   • [claimed-docs] “OpenCode integrates with your GitHub workflow. Mention /opencode or /oc in your comment, and OpenCode will execute tasks within your GitHub …”
   • [claimed-docs] “This agent is useful when you want the LLM to analyze code, suggest changes, or create plans without making any actual modifications to your…”
   • [claimed-docs] “A fast, read-only agent for exploring codebases. Cannot modify files.”
   • [claimed-docs] “This will walk you through installing the GitHub app, creating the workflow, and setting up secrets.”

   proof ↗⚑ flag

3. developerInspect diffs and run checks to catch problems before merging

   weight 3 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   Copilot provides code review with inline suggested changes and severity-labeled comments (docs-28, docs-29), integrated with PR diffs, plus Autofix for vulnerability detection (docs-13) and agent mode validation of files (docs-22). This directly supports inspecting diffs and catching problems pre-merge. Missing for 10: independent/hands-on evidence of the code-review feature's real-world accuracy and no explicit mention of running CI/test checks as part of the flow.

   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”
   • [claimed-docs] “GitHub Copilot Autofix provides contextual explanations and code suggestions to help developers fix vulnerabilities in code”
   • [claimed-docs] “Copilot in your editor does it all, from explaining concepts and completing code, to proposing edits and validating files with agent mode.”
   • [claimed-docs] “Access to Cloud agent and code review”

   proof ↗⚑ flag

   OpenCode~partialclaimed4/10

   OpenCode offers a read-only 'plan' agent for reviewing suggested changes without applying them and a permission system that can prompt before actions run, plus GitHub PR/Actions integration for submitting changes — these provide some review-safety scaffolding. However there is no documented diff-viewing UI or built-in test/lint/check-running capability before merge. Missing for 10: explicit diff inspection tooling, integrated test/lint/CI check execution, and independent evidence that these safety mechanisms actually prevent bad merges.

   • [claimed-docs] “Use the plan agent to analyze code and review suggestions without making any code changes.”
   • [claimed-docs] “This agent is useful when you want the LLM to analyze code, suggest changes, or create plans without making any actual modifications to your…”
   • [claimed-docs] “A fast, read-only agent for exploring codebases. Cannot modify files.”
   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Ask OpenCode to fix an issue or implement a feature. And it will work in a new branch and submits a PR with all the changes.”
   • [claimed-docs] “Mention `/opencode` or `/oc` in your comment, and OpenCode will execute tasks within your GitHub Actions runner.”

   proof ↗⚑ flag

Safe execution

1. engineering-leadControl which external tools and integrations the agent is allowed to access

   weight 2 · round drawn
   GitHub Copilot✓fullclaimed8/10

   GitHub Copilot provides explicit admin controls to allow-list MCP servers developers can access ('Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access'), plus a centralized control plane with audit logs for governance over agents. This directly matches the engineering-lead's need to restrict external tool/integration access. Missing for 10: independent/hands-on verification of the allow-list enforcement in practice, and more granular detail on per-tool (vs per-MCP-server) restriction scope.

   • [claimed-docs] “Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”
   • [claimed-docs] “Connect MCP servers to Copilot Chat to share context from other applications.”

   proof ↗⚑ flag

   OpenCode✓fullclaimed8/10

   OpenCode's permission system lets leads set actions to auto-run, prompt, or block per tool/input, and MCP servers (external tools) are explicitly added/configured (docs-4/23/41). Enterprise config also lets orgs force use of an internal AI gateway and SSO, further restricting what integrations agents can reach (docs-33/50). Missing for 10: independent/hands-on confirmation that permission rules reliably block disallowed MCP tool calls in practice, and finer detail on allow/deny lists for specific external tool names beyond the general permission object.

   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “OpenCode uses the permission config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Start OpenCode with --auto to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “For most permissions, you can use an object to apply different actions based on the tool input.”
   • [claimed-docs] “Use external_directory to allow tool calls that touch paths outside the working directory where OpenCode was started.”
   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP. OpenCode supports both local and remote servers.”
   • [claimed-docs] “You can add external tools to OpenCode using the Model Context Protocol, or MCP.”
   • [claimed-docs] “You can add external tools to OpenCode using the _Model Context Protocol_, or MCP.”
   • [claimed-docs] “This centralized config can integrate with your SSO provider and ensures all users access only your internal AI gateway.”
   • [claimed-docs] “Through the central config, OpenCode can integrate with your organization’s SSO provider for authentication.”

   proof ↗⚑ flag

2. engineering-leadHave the agent operate inside a sandbox when interacting with code, tools, and network resources

   weight 2 · round to GitHub Copilot
   GitHub Copilot✓fullclaimed8/10

   Docs explicitly state that Cloud and local sandboxes provide isolated execution environments letting Copilot safely interact with code, tools, filesystem, and network resources, either locally or in fully isolated cloud environments, with additional governance controls like MCP server allow lists and audit logs. Missing for 10: independent/hands-on verification of sandbox isolation guarantees and no detail on sandbox escape/limits.

   • [claimed-docs] “Cloud and local sandboxes provide isolated execution environments that let Copilot safely interact with code, tools, filesystem, and network…”
   • [claimed-docs] “Control which MCP servers developers can access from their IDEs, and use allow lists to prevent unauthorized access.”
   • [claimed-docs] “Track activity with detailed audit logs and enforce governance by managing agents from a single control plane.”

   proof ↗⚑ flag

   OpenCode—none0/10

   OpenCode's documentation only describes a permission system (auto-approve/prompt/block) and an 'external_directory' toggle for path access — not an isolated sandbox for code execution, tool calls, or network access. Community evidence (opencode-comm-18) even flags that the local server mode allows any local process or webpage to execute code without authentication, the opposite of sandboxed isolation, and there is no first-party claim of container/VM-based sandboxing to dispute.

   • [claimed-docs] “OpenCode uses the `permission` config to decide whether a given action should run automatically, prompt you, or be blocked.”
   • [claimed-docs] “Start OpenCode with `--auto` to automatically approve permission requests that are not explicitly denied.”
   • [claimed-docs] “Use external_directory to allow tool calls that touch paths outside the working directory where OpenCode was started.”
   • [community] “When server is enabled, any web page served from localhost/127.0.0.1 can execute code; any local process can execute code without authentica…”

   proof ↗⚑ flag

Security checks

1. engineering-leadSee license and public-code matching references for AI-suggested code

   weight 1 · round to GitHub Copilot
   GitHub Copilot~partialcommunity5/10

   GitHub Copilot documents a public-code matching feature that searches public GitHub repos for matches to a suggestion (docs-11), which is the closest evidence to the story's ask. However, the evidence pack gives no detail on how license attribution is actually surfaced to an engineering lead, and community discussion raises real concerns about verbatim/near-verbatim reproduction and licensing risk (comm-12, comm-13, comm-14, comm-16), with only partial rebuttal (comm-17) — indicating the feature's coverage and reliability for license-safety review is limited. Missing for 10: detailed docs on license display/attribution UI, audit/reporting workflow for engineering leads, and independent verification that the matching feature reliably flags copyleft/licensed snippets.

   • [claimed-docs] “This feature searches across public GitHub repositories for code that matches a Copilot suggestion.”
   • [community] “It certainly seems to be a laundering enabler. Say that you want to un-GPL-ify some famous copylefted code... you type a first innocuous cha…”
   • [community] “The potential inclusion of GPL'd code, and potentially even unlicensed code, is making me wary of using it. Fair Use doesn't exist here and …”
   • [community] “'We found that about 0.1% of the time, the suggestion may contain some snippets that are verbatim from the training set.' If it's spitting o…”
   • [community] “I just tested it myself on a random c file... it reproduced his full code verbatim from just the function header so clearly it does regurgit…”
   • [community] “It prints this code because you have it open in another editor tab. Wish people who don't know at all how it works stopped acting all outrag…”

   proof ↗⚑ flag

   OpenCode—none0/10

   No evidence of any license or public-code matching/attribution feature for AI-suggested code in OpenCode's docs or community reports; the product focuses on agent workflows, permissions, and MCP integration but nothing about code provenance or license scanning.

   ⚑ flag

2. developerGet contextual explanations and automatic fixes for security vulnerabilities

   weight 2 · round to GitHub Copilot
   GitHub Copilot~partialclaimed6/10

   GitHub Copilot Autofix is explicitly documented to provide 'contextual explanations and code suggestions to help developers fix vulnerabilities in code' and Copilot code review adds severity-labeled feedback with suggested fixes, directly matching the story. However, this is first-party documentation only with no independent/hands-on validation of Autofix's real-world effectiveness, and no detail on scope/limitations (e.g., which languages, integration with Advanced Security). missing for 10: independent corroboration of Autofix accuracy, hands-on developer reports validating the fix quality, details on prerequisites/limitations of the feature.

   • [claimed-docs] “GitHub Copilot Autofix provides contextual explanations and code suggestions to help developers fix vulnerabilities in code”
   • [claimed-docs] “GitHub Copilot can review your code and provide feedback. Where possible, Copilot's feedback includes suggested changes which you can apply …”
   • [claimed-docs] “Copilot labels each comment with a severity level of "High," "Medium," or "Low" to help you prioritize the issues it finds based on their im…”

   proof ↗⚑ flag

   OpenCode—none0/10

   OpenCode is a general coding agent with plan/explore/build agents and permission controls, but no evidence describes any security-vulnerability scanning, contextual vulnerability explanations, or automatic security fix generation as a feature. Community evidence even highlights unresolved security reports and vulnerabilities in OpenCode itself, not a capability to detect/fix vulnerabilities in user code.

   ⚑ flag