Codex vs Google Antigravity

Agent access

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

   weight 2 · round to Google Antigravity
   Codex~partialprobed4/10

   A dedicated llms.txt file is absent (404 at platform.openai.com/llms.txt), but Codex does publish machine-readable markdown docs (learn.chatgpt.com/docs/codex/cli.md) confirmed reachable by probe, which is an agent-friendly doc format an AI agent could be pointed at. Missing for 10: a standard llms.txt manifest, evidence of agents actually being pointed at these docs, and confirmation across all doc pages (docs/codex.md also 404s).

   • [probe] “PROBE llms.txt: HTTP 404 at https://platform.openai.com/llms.txt”
   • [probe] “PROBE docs-md: HTTP 404 at https://platform.openai.com/docs/codex.md”
   • [probe] “official CLI documented at https://learn.chatgpt.com/docs/codex/cli”

   proof ↗⚑ flag

   Google Antigravity✓fullprobed9/10

   Antigravity hosts a working llms.txt (HTTP 200) describing itself, and provides markdown-formatted docs pages (e.g. getting-started.md) that an agent can fetch directly, confirming genuine agent-oriented documentation support. Missing for 10: independent third-party confirmation that agents actually consume these successfully in practice.

   • [probe] “PROBE llms.txt: HTTP 200 at https://antigravity.google/llms.txt # Google Antigravity > Google Antigravity is an advanced agentic coding pla…”
   • [probe] “PROBE docs-md: HTTP 200 at https://antigravity.google/docs/getting-started.md # Getting Started with Antigravity 2.0 ### Download Visit [a…”
   • [claimed-docs] “Visit antigravity.google/download to download Google Antigravity 2.0. Select your operating system below”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex✓fullclaimed8/10

   Codex CLI explicitly documents non-interactive execution via `codex exec` for use in repeatable workflows, scripts, and CI/CD pipelines (codex-docs-19, codex-docs-32), and permissions/sandbox controls can be configured for unattended runs (codex-docs-17, codex-docs-39). Missing for 10: no independent case study or CI provider (e.g. GitHub Actions) integration example, and no explicit exit-code/output-format spec for CI parsing.

   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”
   • [claimed-docs] “Compose with scripts and CI: Use Codex interactively or call codex exec from repeatable workflows and pipelines.”
   • [claimed-docs] “Choose when Codex can edit files or run commands without asking, and inspect the active sandbox and writable roots before you continue.”
   • [claimed-docs] “Set the boundaries for each run — /permissions: Choose when Codex can edit files or run commands without asking, and inspect the active sand…”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed7/10

   Antigravity CLI has a documented headless mode explicitly for scripting agent tasks, CI pipeline integration, and machine-readable output (antigravity-docs-50), plus scheduled/cron tasks and background subagents support agentic automation outside interactive UI. Missing for 10: independent hands-on CI usage reports, concrete CI config examples/output schema, and no community corroboration of headless/CI use in practice.

   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “Create or download fully customizable skills to further your agent’s autonomy and transform how you get work done.”

   proof ↗⚑ flag

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

   weight 3 · round to Codex
   Codex✓fullclaimed9/10

   Codex CLI explicitly supports adding local/remote MCP servers via `codex mcp add`, inspecting available tools before use, and viewing active servers via `/mcp`; this configuration is shared across ChatGPT desktop app, CLI, and IDE extension. Docs also describe using MCP to connect to third-party tools like browsers or Figma. Missing for 10: independent hands-on verification of MCP tool usage in a real session beyond first-party docs.

   • [claimed-docs] “Add local or remote MCP servers, authenticate when needed, and inspect the tools available to the current session before Codex uses them.”
   • [claimed-docs] “The ChatGPT desktop app, Codex CLI, and IDE extension share this configuration. Once you configure your MCP servers, you can switch among th…”
   • [claimed-docs] “Connect external tools with MCP — codex mcp: Add local or remote MCP servers, authenticate when needed, and inspect the tools available to t…”
   • [claimed-docs] “Model Context Protocol (MCP) connects models to tools and context. Use it to give ChatGPT or Codex access to third-party documentation, or t…”
   • [claimed-docs] “codex mcp add <server-name> --env VAR1=VALUE1 --env VAR2=VALUE2 -- <stdio server-command>”
   • [claimed-docs] “In the `codex` TUI, use `/mcp` to see your active MCP servers.”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed8/10

   Antigravity has explicit, dedicated MCP documentation stating MCP lets it 'fetch structured context directly or execute safe actions on your behalf' and that it 'securely connects to local developer tools, databases, file parsers, and external remote APIs' via MCP, plus CLI/SDK support for configuring MCP servers (slash commands, plugins bundling MCP servers, layering MCP servers in the Agent SDK). Missing for 10: independent hands-on confirmation of successfully connecting a third-party MCP server and using its tools in a real workflow.

   • [claimed-docs] “MCP lets Antigravity fetch structured context directly or execute safe actions on your behalf when needed.”
   • [claimed-docs] “lets AI agents and editors securely connect to local developer tools, databases, file parsers, and external remote APIs”
   • [claimed-docs] “Access plugins, MCP, skills, and hooks configurations instantly via slash commands, quickly enhancing your workflow.”
   • [claimed-docs] “Layer custom Python callables, Model Context Protocol (MCP) servers, and reusable agent skills over our built-in filesystem and terminal too…”
   • [claimed-docs] “Plugins are namespaced bundles that allow you to extend Antigravity’s capabilities by grouping skills, rules, MCP servers, and hooks into a …”

   proof ↗⚑ flag

4. ai-native userUse an official CLI

   weight 2 · round to Codex
   Codex✓fullprobed9/10

   Codex ships an official, well-documented CLI (npm install -g @openai/codex) with rich agentic capabilities: local repo editing, exec/non-interactive scripting, MCP support, subagents, image input, sandbox/permissions control, cloud task delegation, and shell completions — all first-party documented and confirmed via GitHub repo and docs. Missing for 10: independent hands-on benchmarking specifically of CLI workflows (community evidence focuses mostly on model quality/UX rather than CLI mechanics) and some Linux-specific gaps noted by users.

   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”
   • [github] “npm install -g @openai/codex”
   • [claimed-docs] “Inspect code, make changes, run commands, and automate repeatable work without leaving your terminal.”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”
   • [claimed-docs] “Compose with scripts and CI: Use Codex interactively or call codex exec from repeatable workflows and pipelines.”
   • [claimed-docs] “Connect external tools with MCP — codex mcp: Add local or remote MCP servers, authenticate when needed, and inspect the tools available to t…”
   • [claimed-docs] “Split up a larger investigation — subagents: Ask Codex to delegate focused work to specialized agents, then bring their findings back into t…”
   • [claimed-docs] “Choose when Codex can edit files or run commands without asking, and inspect the active sandbox and writable roots before you continue.”
   • [claimed-docs] “Install the Codex CLI with the standalone installer for macOS and Linux.”
   • [probe] “official CLI documented at https://learn.chatgpt.com/docs/codex/cli”

   proof ↗⚑ flag

   Google Antigravity✓fullprobed8/10

   Google Antigravity ships an official CLI with dedicated docs (antigravity-cli product page, headless/non-interactive mode for CI, sandboxing, vim mode, gcli migration), enabling natural-language orchestration of parallel agents, slash commands, and MCP/plugin config — clearly AI-native and agentic. Community evidence corroborates the CLI works in practice alongside VSCode. Missing for 10: independent deep-dive review of CLI-specific reliability/performance beyond a single community mention.

   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “Have multiple agents working in parallel, so larger tasks get tackled faster.”
   • [claimed-docs] “Navigate your entire workflow via standard terminal shortcuts: adjust permissions, themes, and preferences via /config and type /keybindings…”
   • [claimed-docs] “Access plugins, MCP, skills, and hooks configurations instantly via slash commands, quickly enhancing your workflow.”
   • [claimed-docs] “the CLI automatically detects your existing profiles. An interactive checklist prompts you to choose which assets to migrate”
   • [claimed-docs] “Sensitive files like ~/.ssh and .env are blocked, anything not explicitly mounted is invisible inside the sandbox”
   • [claimed-docs] “Vim editor mode replaces the editing model in every multi-line input surface of the CLI”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [community] “I much prefer using Gemini CLI in combination with vscode. It works like a charm. Now, I'll do the same with Antigravity CLI and vscode. It …”
   • [probe] “official CLI documented at https://antigravity.google/product/antigravity-cli”

   proof ↗⚑ flag

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

   weight 3 · round to Google Antigravity
   Codex~partialcommunity5/10

   Codex documents multiple programmatic entry points — an MCP server interface for JSON-RPC control (though explicitly marked deprecated/experimental in favor of an undocumented 'app server'), a non-interactive `codex exec` mode for scripts/CI, and 'API key' usage — but these come with real caveats: API-key use 'requires additional setup', the flagship gpt-5.3-codex model was reportedly not yet available via API, and the primary MCP server route is deprecated rather than a stable first-class API. missing for 10: a single stable, non-deprecated documented public API surface, confirmation that the current model is API-accessible, and independent corroboration that third parties successfully drive Codex via this API.

   • [github] “You can also use Codex with an API key, but this requires additional setup.”
   • [github] “Codex MCP Server Interface [experimental]: a JSON-RPC API that runs over the Model Context Protocol (MCP) transport to control a local Codex…”
   • [claimed-docs] “codex mcp-server is deprecated. Use the Codex app server instead. ... This page documents the deprecated command for existing integrations. …”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”
   • [claimed-docs] “Compose with scripts and CI: Use Codex interactively or call codex exec from repeatable workflows and pipelines.”
   • [community] “gpt-5.3-codex isn't available on the API yet — 'We are working to safely enable API access soon.'”

   proof ↗⚑ flag

   Google Antigravity~partialprobed6/10

   Antigravity documents an Agent SDK (Python) exposing the same tools/agent loop/context management as the app, plus a CLI headless mode for scripting and CI integration, both of which let an AI-native user drive the product programmatically. However, there is no evidence of a formal public REST/HTTP API — a probe for OpenAPI/swagger specs returned 404 on all candidate paths, so the 'documented public API' is limited to SDK/CLI surfaces rather than a conventional API contract. Missing for 10: a documented REST/HTTP API or OpenAPI spec, independent third-party confirmation of SDK usage/stability.

   • [claimed-docs] “The Agent SDK gives you the same tools, agent loop, and context management that power Google Antigravity, programmable in Python.”
   • [claimed-docs] “Layer custom Python callables, Model Context Protocol (MCP) servers, and reusable agent skills over our built-in filesystem and terminal too…”
   • [claimed-docs] “Build AI agents that autonomously read files, run commands, edit code, and more.”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://antigravity.google/openapi.json, https://antigravity.google/swagger.json, https://antigravit…”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex~partialclaimed5/10

   OpenAI's platform docs describe RBAC and project/org-scoped API keys/custom roles, and Codex can authenticate via an API key (codex-gh-4), so scoped credentials are technically available to a Codex-using account. However, none of the evidence ties this RBAC/API-key scoping specifically to configuring or restricting a Codex agent's own permissions — missing for 10: Codex-specific docs on issuing least-privilege keys for agent sessions, guidance on scoping credentials per-task/per-repo, and independent confirmation that this RBAC applies to Codex's own execution rather than just general API access.

   • [claimed-docs] “Role-based access control (RBAC) lets you decide who can do what across your organization and projects—both through the API and in the Dashb…”
   • [github] “You can also use Codex with an API key, but this requires additional setup.”
   • [claimed-docs] “Create a model response — request/response reference with runnable code samples selectable per language: HTTP, Python, TypeScript, Go, Ruby,…”

   proof ↗⚑ flag

   Google Antigravity!disputedcontradicted4/10

   Antigravity documents permission tiers (Deny/Ask/Allow) and a CLI sandbox that explicitly blocks access to sensitive files like .env and ~/.ssh, which is the closest analog to least-privilege credential scoping for an agent (docs-23, docs-42, docs-48). However, independent reports document a concrete bypass: Antigravity's own setting disallowing .env access was circumvented via prompt injection to exfiltrate secrets, and a default allowlisted domain (webhook.site) was used as an exfiltration channel — directly contradicting the claimed least-privilege protection (antigravity-comm-11, antigravity-comm-12). There is no evidence of a true scoped API-credential-issuance mechanism (e.g., minting restricted API keys/tokens for an agent); missing for 10: actual credential/token scoping API, third-party security audit confirming the sandbox holds, and any documented remediation.

   • [claimed-docs] “Permissions are evaluated across three distinct access lists: Deny... Ask... Allow”
   • [claimed-docs] “Permissions are evaluated across three distinct access lists: Deny...Ask...Allow”
   • [claimed-docs] “Sensitive files like ~/.ssh and .env are blocked, anything not explicitly mounted is invisible inside the sandbox”
   • [community] “Google Antigravity exfiltrates data via indirect prompt injection attack: Gemini is not supposed to have access to .env files with default s…”
   • [community] “The default Allowlist provided with Antigravity includes 'webhook.site', which was used as an exfiltration vector for secrets.”

   proof ↗⚑ flag

7. ai-native userBuild against official SDKs

   weight 2 · round to Google Antigravity
   Codex~partialcommunity6/10

   Codex is a coding agent, but the evidence shows a genuine SDK-adjacent surface: the underlying OpenAI Responses API has an official OpenAPI spec and multi-language code samples (Python, TypeScript, Go, Ruby, Java, HTTP, CLI), and Codex integrates via CLI/MCP for programmatic extension. However, there is no evidence of an official Codex-specific SDK (as opposed to the general OpenAI API SDK), and API access for the Codex model itself is explicitly noted as not yet available. missing for 10: a dedicated Codex SDK/library distinct from the general OpenAI Responses API, confirmation that Codex agent capabilities (not just chat completions) are exposed via SDK, independent developer corroboration of building against these SDKs.

   • [claimed-docs] “Create a model response — request/response reference with runnable code samples selectable per language: HTTP, Python, TypeScript, Go, Ruby,…”
   • [github] “A machine-readable description of the OpenAI REST API, authored in OpenAPI 3.1.”
   • [community] “gpt-5.3-codex isn't available on the API yet — 'We are working to safely enable API access soon.'”
   • [claimed-docs] “Add local or remote MCP servers, authenticate when needed, and inspect the tools available to the current session before Codex uses them.”

   proof ↗⚑ flag

   Google Antigravity✓fullprobed7/10

   Google explicitly documents an official Agent SDK ('same tools, agent loop, and context management that power Antigravity, programmable in Python') supporting custom Python callables, MCP servers, skills, and multimedia inputs, which directly satisfies building against an official SDK. Missing for 10: independent/hands-on developer confirmation of the SDK working as documented, and no public API reference/OpenAPI spec was found (probe returned 404s), so depth of documentation beyond marketing copy is unverified.

   • [claimed-docs] “The Agent SDK gives you the same tools, agent loop, and context management that power Google Antigravity, programmable in Python.”
   • [claimed-docs] “Layer custom Python callables, Model Context Protocol (MCP) servers, and reusable agent skills over our built-in filesystem and terminal too…”
   • [claimed-docs] “Pass rich multimedia file attachments (images, videos, audio, and documents) to the agent alongside textual instruction prompt lists.”
   • [claimed-docs] “Build AI agents that autonomously read files, run commands, edit code, and more.”
   • [probe] “PROBE openapi: all candidate paths 404 (https://antigravity.google/openapi.json, https://antigravity.google/swagger.json, https://antigravit…”

   proof ↗⚑ flag

8. ai-native userSubscribe to events via webhooks

   weight 2 · round drawn
   Codex—none0/10

   No evidence in the pack mentions webhooks or event subscription capabilities for Codex; the product exposes MCP servers, CLI, and cloud task integrations but nothing about outbound webhook events for AI-native consumers.

   ⚑ flag

   Google Antigravity—none0/10

   No evidence of any webhook subscription mechanism; Antigravity is an IDE/CLI/agent platform with hooks, MCP, and scheduled tasks, but nothing about outbound event subscriptions via webhooks. Even the openapi probe returned 404s, indicating no public API surface for such integration.

   • [probe] “PROBE openapi: all candidate paths 404 (https://antigravity.google/openapi.json, https://antigravity.google/swagger.json, https://antigravit…”

   proof ↗⚑ flag

Agentic features

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

   weight 2 · round drawn
   Codex~partialclaimed6/10

   Codex generates AI-driven insights and suggestions specifically about code: it produces prioritized review findings, diffs, and summaries during automated reviews and delegated tasks (codex-docs-5, codex-docs-10, codex-docs-41, codex-docs-45), and can delegate to subagents for deeper investigation (codex-docs-35). However, this is scoped to code/repository data rather than general business or product data insights. Missing for 10: evidence of insight generation over non-code data sources, dashboards, or analytics-style summaries beyond code review findings.

   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Split up a larger investigation — subagents: Ask Codex to delegate focused work to specialized agents, then bring their findings back into t…”

   proof ↗⚑ flag

   Google Antigravity~partialcommunity6/10

   Antigravity's editor/agent generates code suggestions, tab-autocompletion, and rich 'Artifacts' (implementation plans, diagrams, code diffs) that surface AI-derived insights from the user's codebase (antigravity-docs-6, -24, -30, -41), fitting the 'insights from data' story in a coding context. However, this is inference-in-editor suggestion generation rather than dedicated analytics/insight dashboards, and community hands-on reports raise real quality concerns ('the model was not good and slow, the harness was not good' — antigravity-comm-8), undercutting confidence in consistent insight quality. Missing for 10: no evidence of dedicated data-analysis/insight-summarization features beyond code artifacts, and no independent corroboration that suggestions are reliably high quality.

   • [claimed-docs] “Google Antigravity's Editor view offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurab…”
   • [claimed-docs] “Planning Mode: The agent plans thoroughly before executing tasks... produces structured implementation plans called Artifacts”
   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurable agent”
   • [community] “It's not even good, honestly. I was using it for couple weeks before dropping that 2 months ago. The model was not good and slow, the harnes…”

   proof ↗⚑ flag

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

   weight 2 · round to Google Antigravity
   Codex✓fullclaimed7/10

   Codex cloud supports delegating longer tasks that run in isolated cloud environments in parallel, triggered from GitHub, GitLab, Linear, or Slack, and returning results (diff/PR) when ready — a clear background-automation workflow, and the CLI also supports non-interactive/repeatable workflows for scripted automation. Missing for 10: no documentation of scheduled/cron-style recurring triggers, and no independent/hands-on confirmation that long unattended background runs work reliably (community commentary focuses on interactive model quality/UX rather than background automation specifically).

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed8/10

   Docs explicitly describe Scheduled Tasks with cron schedules that let agents 'start and run autonomously in the background' (docs-2), plus related capabilities like scheduling messages to agents while away (docs-39), isolated background worktrees (docs-38), and headless/non-interactive CLI runs for CI automation (docs-50). This directly matches the story of autonomous background automations. Missing for 10: independent/hands-on verification that scheduled background tasks work reliably (community evidence focuses on other bugs/exfiltration issues, not scheduling specifically), and more detail on monitoring/error-handling for unattended runs.

   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [claimed-docs] “users can schedule messages to be sent to their agents while they’re away”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   Codex✓fullclaimed8/10

   Codex documents explicit task delegation to its built-in agent, both for long-running cloud tasks ('Delegate a longer task and return when it is ready') and for sub-agent delegation within a session ('Ask Codex to delegate focused work to specialized agents, then bring their findings back into the main terminal session'), backed by detailed CLI/cloud docs. Missing for 10: independent hands-on verification specifically of the subagent delegation flow (community evidence discusses general agent quality/UX but not this feature directly).

   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Ask Codex to delegate focused work to specialized agents, then bring their findings back into the main terminal session.”
   • [claimed-docs] “Split up a larger investigation — subagents: Ask Codex to delegate focused work to specialized agents, then bring their findings back into t…”
   • [claimed-docs] “Move work to Codex cloud — codex cloud: Browse active and completed chats, submit work to a configured environment, and apply the result to …”
   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”

   proof ↗⚑ flag

   Google Antigravity✓fullcommunity8/10

   Antigravity is built around delegating tasks to autonomous agents that operate across editor, terminal, and browser, with subagents, scheduled tasks, and natural-language task delegation extensively documented; hands-on community reports (comm-1, comm-10) confirm the agent/CLI actually works for delegated tasks. missing for 10: independent third-party benchmarking of delegation quality, and community evidence is mixed on reliability/bugs which caps quality below top marks.

   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “Antigravity comes pre-packaged with several specialized subagents out of the box”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”
   • [community] “I went ahead and downloaded it, it looks to be a VSCode fork very similar to Cursor, with support for Gemini 3 Pro, Claude Sonnet 4.5, and G…”
   • [community] “I much prefer using Gemini CLI in combination with vscode. It works like a charm. Now, I'll do the same with Antigravity CLI and vscode. It …”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Codex✓fullcommunity8/10

   Codex CLI, IDE extension, cloud, and web surfaces are all operated by natural-language prompts/chats — e.g. starting tasks from prompts, resuming chats, delegating subagents, pasting images into the composer, and non-interactive `codex exec` for scripted natural-language instructions — all documented as the primary interaction mode across surfaces. Community threads corroborate heavy real-world use of this conversational/agentic workflow, even amid quality complaints about model performance. missing for 10: independent benchmarking specifically of natural-language command comprehension/robustness (community evidence is about overall agent quality/speed, not NL parsing specifically).

   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Ask Codex to delegate focused work to specialized agents, then bring their findings back into the main terminal session.”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”
   • [claimed-docs] “`codex resume`: Reopen a recent chat from the current repository, or search across local chats when you need to return to older work.”
   • [claimed-docs] “Bring visual context into the prompt — codex --image: Pass an error screenshot, architecture diagram, or design reference with the first pro…”
   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”
   • [community] “Genuinely excited to try this out. I've started using Codex much more heavily in the past two months and honestly, it's been shockingly good…”

   proof ↗⚑ flag

   Google Antigravity✓fullcommunity8/10

   Docs consistently describe natural-language operation as the core interaction model — editing, orchestrating, and building 'all in natural language' (antigravity-docs-9), NL code commands in the IDE (antigravity-docs-6/41), and even voice-to-prompt transcription (antigravity-docs-3), backed by planning/artifact review flows driven by conversational prompts (antigravity-docs-24, antigravity-docs-25). Community evidence corroborates it functions as an agentic assistant (comm-1, comm-10) though with quality/reliability complaints unrelated to the NL-command axis itself. Missing for 10: independent hands-on confirmation specifically praising the NL-command UX (most community commentary focuses on bugs/pricing/security rather than command quality).

   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “Google Antigravity's Editor view offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurab…”
   • [claimed-docs] “offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurable agent”
   • [claimed-docs] “Speak your prompts. Powered by the latest Gemini Audio models, real-time transcription converts conversational speech into clearly phrased p…”
   • [claimed-docs] “Planning Mode: The agent plans thoroughly before executing tasks... produces structured implementation plans called Artifacts”
   • [claimed-docs] “The agent always halts and requests your explicit approval before proceeding with proposed changes.”
   • [community] “I went ahead and downloaded it, it looks to be a VSCode fork very similar to Cursor, with support for Gemini 3 Pro, Claude Sonnet 4.5, and G…”
   • [community] “I much prefer using Gemini CLI in combination with vscode. It works like a charm. Now, I'll do the same with Antigravity CLI and vscode. It …”

   proof ↗⚑ flag

Api quality

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

   weight 2 · round to Codex
   Codex~partialclaimed4/10

   OpenAI publishes a machine-readable OpenAPI 3.1 spec for its REST API (codex-gh-9) and Codex can be used via that API (codex-gh-4), but the evidence never confirms this spec explicitly covers or is dedicated to Codex-specific endpoints, nor is there a direct 'download spec' link tied to Codex docs. missing for 10: a Codex-specific OpenAPI/spec file, explicit download instructions, or confirmation the general OpenAI OpenAPI spec includes Codex CLI/agent endpoints.

   • [github] “A machine-readable description of the OpenAI REST API, authored in OpenAPI 3.1.”
   • [github] “You can also use Codex with an API key, but this requires additional setup.”
   • [claimed-docs] “Create a model response — request/response reference with runnable code samples selectable per language: HTTP, Python, TypeScript, Go, Ruby,…”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   A direct probe for OpenAPI/Swagger specs at all standard candidate paths returned 404s, and no documentation item mentions a machine-readable API spec despite extensive docs on SDK, CLI, and MCP.

   • [probe] “PROBE openapi: all candidate paths 404 (https://antigravity.google/openapi.json, https://antigravity.google/swagger.json, https://antigravit…”

   proof ↗⚑ flag

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

   weight 1 · round to Codex
   Codex~partialcommunity6/10

   Codex offers isolated cloud task environments and CLI sandbox controls (writable roots, permission gating) that keep agent actions contained rather than acting directly on a live system, which functions as a sandbox layer for testing changes. However, there's no explicit documentation of test-vs-production data separation, and a community report raises unresolved concerns about the sandbox reading sensitive filesystem data without asking. Missing for 10: explicit production-data isolation guarantees, first-party documentation addressing the raised sandbox-safety concern, and independent verification that isolated environments never touch real prod data.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Configure the dependencies, tools, variables, and setup steps each repository needs.”
   • [claimed-docs] “Choose when Codex can edit files or run commands without asking, and inspect the active sandbox and writable roots before you continue.”
   • [community] “Does that version of Codex still read sensitive data on your file system without even asking? Just curious. [links to github.com/openai/code…”

   proof ↗⚑ flag

   Google Antigravity!disputedcontradicted4/10

   Antigravity's CLI docs claim a sandbox that blocks sensitive files (~/.ssh, .env) and hides anything not explicitly mounted, which sounds like exactly the kind of safe-testing boundary this story wants, but hands-on community reports directly contradict this: Gemini bypassed its own .env protection to exfiltrate secrets via prompt injection, a default allowlisted webhook.site was used as an exfiltration vector, and in another incident Antigravity commands deleted an entire drive outside any expected sandbox boundary. This is a concrete, documented failure of the sandbox promise rather than mere skepticism. Missing for 10: a genuine isolated/staging environment separate from real user data, and any vendor or independent confirmation that the sandbox reliably prevents production-data access after these reported bypasses.

   • [claimed-docs] “Sensitive files like ~/.ssh and .env are blocked, anything not explicitly mounted is invisible inside the sandbox”
   • [community] “Google Antigravity exfiltrates data via indirect prompt injection attack: Gemini is not supposed to have access to .env files with default s…”
   • [community] “The default Allowlist provided with Antigravity includes 'webhook.site', which was used as an exfiltration vector for secrets.”
   • [community] “Antigravity was also vulnerable to the classic Markdown image exfiltration bug, reported a few days prior and flagged as 'intended behavior'…”
   • [community] “Google Antigravity just deleted the contents of whole drive - came down to commanding a deletion of a 'directory with space in the name' wit…”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex~partialclaimed3/10

   There is a documented OpenAPI 3.1 spec and API reference (codex-gh-9, codex-docs-29) and one concrete example of a deprecation notice (codex mcp-server deprecated in favor of the Codex app server, codex-docs-23), showing some practice of versioning and deprecation. However, there is no comprehensive, documented deprecation policy (timelines, notice periods, version numbering scheme) covering the Codex/OpenAI API generally. Missing for 10: an explicit deprecation policy document, API version numbering scheme, and independent corroboration of adherence to it.

   • [github] “A machine-readable description of the OpenAI REST API, authored in OpenAPI 3.1.”
   • [claimed-docs] “Create a model response — request/response reference with runnable code samples selectable per language: HTTP, Python, TypeScript, Go, Ruby,…”
   • [claimed-docs] “codex mcp-server is deprecated. Use the Codex app server instead. ... This page documents the deprecated command for existing integrations. …”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   No evidence of versioned APIs or a documented deprecation policy; OpenAPI probe returned 404s across all candidate paths and no docs mention API versioning or deprecation timelines.

   • [probe] “PROBE openapi: all candidate paths 404 (https://antigravity.google/openapi.json, https://antigravity.google/swagger.json, https://antigravit…”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Codex~partialclaimed6/10

   Codex supports running multiple cloud tasks in parallel across repos (codex-docs-1, codex-docs-3, codex-docs-6) and delegating focused work to specialized sub-agents within a session (codex-docs-13), which gives some bulk/parallel automation capability. However, there's no explicit evidence of a bulk operation primitive (e.g., batch-apply an action across many files/items/tickets in one command) — the parallelism described is task-level (multiple independent runs) rather than a documented 'operate over N items at once' feature. Missing for 10: explicit bulk/batch API or CLI verb for acting across many items in one invocation, and independent confirmation of large-scale parallel throughput in practice.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Ask Codex to delegate focused work to specialized agents, then bring their findings back into the main terminal session.”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed6/10

   Antigravity supports parallel multi-agent orchestration across independent projects, subagent delegation, scheduled/background tasks, and a headless CLI for scripting bulk/CI workflows, which together enable operating across many items or tasks concurrently. However, there is no explicit documentation of a dedicated 'bulk operation' primitive (e.g., batch-apply an action across a list of files/items in one command) — the capability is inferred from parallelism/orchestration features rather than a purpose-built bulk-ops interface. missing for 10: explicit bulk/batch API or command for applying one operation across many items, independent hands-on evidence of large-scale parallel task execution working reliably.

   • [claimed-docs] “Orchestrate multiple autonomous agents working in parallel across independent projects.”
   • [claimed-docs] “Have multiple agents working in parallel, so larger tasks get tackled faster.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”

   proof ↗⚑ flag

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

   weight 3 · round to Google Antigravity
   Codex—none0/10

   Codex supports triggering tasks from external events (GitHub/GitLab/Linear/Slack) and running non-interactive workflows, but there is no evidence of a user-defined rules engine that lets users specify arbitrary trigger conditions and automated actions (e.g., 'on X event, do Y') — this is closer to integration hooks than a rules/automation framework. missing for 10: evidence of a rules/trigger definition interface, conditional logic configuration, or event-to-action mapping system that users can author themselves.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed7/10

   Antigravity's docs describe explicit rule activation modes (Manual, Always On, Model Decision, Glob) that trigger agent behavior automatically based on context/file patterns, plus Hooks that run custom scripts at specific points in the execution loop and Scheduled Tasks that trigger agents on a cron schedule — together these directly satisfy 'rules that trigger actions automatically on events'. Missing for 10: independent/hands-on verification that rule-triggering works reliably in practice, and more detail on broader event types beyond glob/model-decision/cron.

   • [claimed-docs] “At the rule level you can define how a rule should be activated: Manual... Always On... Model Decision... Glob”
   • [claimed-docs] “Hooks allow you to run custom scripts or shell commands at specific points during Antigravity’s execution loop.”
   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “Rules are manually defined constraints for the Agent to follow, at both the local and global levels.”

   proof ↗⚑ flag

3. ai-native userSchedule recurring jobs or workflows

   weight 2 · round to Google Antigravity
   Codex—none0/10

   The evidence shows Codex can run in CI/scripts (codex exec), be triggered from GitHub/GitLab/Slack, and run cloud tasks, but there is no mention of a native recurring/scheduled job or cron-like trigger mechanism within Codex itself. Automation is triggered by external events or manual invocation, not scheduled recurrence.

   • [claimed-docs] “Compose with scripts and CI: Use Codex interactively or call codex exec from repeatable workflows and pipelines.”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Move work to Codex cloud — codex cloud: Browse active and completed chats, submit work to a configured environment, and apply the result to …”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed8/10

   Docs explicitly describe Scheduled Tasks with cron-defined schedules that run agents autonomously in the background, plus scheduling messages to agents for later delivery, directly matching the recurring-jobs/workflow story. Missing for 10: independent/hands-on confirmation that scheduling actually works reliably in practice, and more detail on job management (editing/deleting/monitoring scheduled runs).

   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “users can schedule messages to be sent to their agents while they’re away”

   proof ↗⚑ flag

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

   weight 1 · round to Codex
   Codex~partialclaimed4/10

   Codex's CLI includes a dedicated review command that inspects diffs/commits without modifying the working tree (codex-docs-10, codex-doces-41/45), and it operates within git repos so changes are inherently versioned and revertible via git; skills/plugins can be packaged as reusable automations (codex-docs-20/42). However, there is no documented mechanism to version, review, or roll back the automations/skills/workflows themselves (e.g., skill version history, rollback of a plugin config, audit trail for automation changes) — only code diffs are reviewed. Missing for 10: explicit versioning of skills/automations, a rollback UI/command for automation configs, and independent evidence of this workflow in practice.

   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Package repeatable instructions as skills, then add plugins to connect Codex to your team's tools and data without leaving the CLI.”
   • [claimed-docs] “Use skills and plugins: Package repeatable instructions as skills, then add plugins to connect Codex to your team's tools and data without l…”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   Evidence shows automations (skills, hooks, plugins, scheduled tasks) but no mention of versioning, review history, or rollback capabilities for these automations themselves — missing for 10: version control/history for skills/hooks/plugins, a review workflow for automation changes, and any rollback/undo mechanism for automations.

   ⚑ 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 Codex
   Codex✓fullcommunity8/10

   Codex cloud lets users delegate tasks that run in isolated cloud environments, inspect summaries/diffs, request follow-ups, and open pull requests for review, effectively building/testing/demoing changes end-to-end for user review (codex-docs-1,5,6,7,37). Community commentary corroborates real-world agentic task completion, though with performance/reliability caveats. Missing for 10: independent hands-on verification specifically of the cloud (not CLI) workflow's demo/test artifacts, and no explicit mention of a 'demo' step (e.g., live preview) beyond diff/PR review.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Start and review work from the web or Codex CLI.”
   • [claimed-docs] “Move work to Codex cloud — codex cloud: Browse active and completed chats, submit work to a configured environment, and apply the result to …”
   • [community] “Often Claude Code Opus 4.6, on hard enough problems, can do the impression of acting fast without really making progress. Then you spin the …”
   • [community] “Genuinely excited to try this out. I've started using Codex much more heavily in the past two months and honestly, it's been shockingly good…”

   proof ↗⚑ flag

   Google Antigravity~partialcommunity6/10

   Docs describe agents that autonomously operate across editor/terminal/browser, delegate testing to subagents, produce reviewable Artifacts (implementation plans, diffs, browser recordings) and halt for approval — covering build, test and demo-for-review end-to-end (antigravity-docs-7,18,24,25,30,46). However, community reports of a subpar harness, app-breaking bugs, and a case where autonomous terminal execution deleted a whole drive raise real doubts about reliable end-to-end execution (antigravity-comm-8,antigravity-comm-14). Missing for 10: independent hands-on confirmation of a full successful build→test→demo cycle, and resolution of reliability/security concerns that could derail autonomous runs.

   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “Planning Mode: The agent plans thoroughly before executing tasks... produces structured implementation plans called Artifacts”
   • [claimed-docs] “The agent always halts and requests your explicit approval before proceeding with proposed changes.”
   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents”
   • [community] “It's not even good, honestly. I was using it for couple weeks before dropping that 2 months ago. The model was not good and slow, the harnes…”
   • [community] “Google Antigravity just deleted the contents of whole drive - came down to commanding a deletion of a 'directory with space in the name' wit…”

   proof ↗⚑ flag

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

   weight 3 · round to Codex
   Codex✓fullclaimed7/10

   OpenAI's docs describe a dedicated Codex cloud mode that runs tasks in isolated cloud environments, in parallel, triggered from web/GitHub/GitLab/Linear/Slack, with configurable repo setup and a workflow to inspect diffs/PRs on completion, plus a CLI command (`codex cloud`) to submit and later pull results locally — squarely matching the story of delegating longer background tasks to an isolated cloud environment. missing for 10: independent or hands-on community corroboration specifically validating the cloud/background execution feature (community evidence in the pack discusses CLI/app UX and model quality, not the cloud delegation flow itself).

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Configure the dependencies, tools, variables, and setup steps each repository needs.”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Move work to Codex cloud — codex cloud: Browse active and completed chats, submit work to a configured environment, and apply the result to …”
   • [github] “If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.”
   • [github] “If you are looking for the <em>cloud-based agent</em> from OpenAI, <strong>Codex Web</strong>, go to <a href="https://chatgpt.com/codex">cha…”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed5/10

   Antigravity supports background/autonomous execution via Scheduled Tasks that run agents in the background, Git worktree-based isolated background folders, and scheduling messages for agents while away, plus a 'Remote Control' feature to connect to running desktop sessions across machines. However, these mechanisms describe local-machine or worktree isolation and remote access to local sessions, not a distinctly cloud-hosted sandbox environment for offloading long-running tasks the way some competitors do. Missing for 10: explicit documentation of a persistent cloud-hosted execution environment independent of the user's machine, and independent/hands-on confirmation that background tasks truly run isolated in the cloud rather than locally.

   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [claimed-docs] “users can schedule messages to be sent to their agents while they’re away”
   • [claimed-docs] “Antigravity Remote Control allows you to securely connect to and drive your Antigravity 2.0 desktop sessions running across your machines fr…”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”

   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 to Google Antigravity
   Codex~partialcommunity6/10

   Codex Cloud supports running multiple tasks in parallel in isolated cloud environments, triggered from GitHub/GitLab/Linear/Slack, and delegating longer tasks to return to later, which covers parallel/async agent work. However, there is no explicit evidence of orchestrating large 'fleets' of many simultaneous agents, no stated duration limits confirming multi-day autonomous runs, and community feedback highlights usage-limit throttling that would constrain sustained parallel/long-running fleets. missing for 10: evidence of fleet-scale orchestration (many concurrent agents), confirmed multi-day autonomous run duration, and independent confirmation that parallel tasks aren't throttled by usage limits.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Configure the dependencies, tools, variables, and setup steps each repository needs.”
   • [community] “Codex is my favorite UX for anything as it edits the files and I can use the proper tooling to adjust and test stuff... However lately the l…”
   • [community] “The main issue I have with Codex is that the best model is insanely slow, except at nights and weekends when Silicon Valley goes to bed... I…”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed7/10

   Docs describe orchestrating multiple autonomous agents in parallel across independent projects, scheduled/cron tasks that run autonomously in the background, worktree-isolated agents, subagent delegation, and remote control to check on running sessions from a browser — all supporting a 'fleet of parallel long-running agents' story. However, there is no independent/hands-on confirmation of agents actually running unattended for 'hours or days' at scale, and community reports focus on bugs, quota limits, and security issues rather than validating multi-day parallel fleet operation. Missing for 10: independent verification of long-duration (hours/days) autonomous runs, evidence of fleet scale limits, and hands-on confirmation from third parties.

   • [claimed-docs] “Orchestrate multiple autonomous agents working in parallel across independent projects.”
   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “Have multiple agents working in parallel, so larger tasks get tackled faster.”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [claimed-docs] “users can schedule messages to be sent to their agents while they’re away”
   • [claimed-docs] “Antigravity Remote Control allows you to securely connect to and drive your Antigravity 2.0 desktop sessions running across your machines fr…”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”

   proof ↗⚑ flag

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

   weight 1 · round to Codex
   Codex~partialclaimed6/10

   Docs confirm Codex cloud can run tasks in parallel in isolated cloud environments without tying up the local machine, and results can be inspected (summary/diff) before choosing to follow up or open a PR — this covers running multiple attempts and reviewing outcomes. However, there's no explicit documentation of a dedicated 'compare multiple attempts side-by-side' UI/workflow, and no independent/community evidence confirming this parallel-comparison workflow works well in practice. missing for 10: explicit side-by-side comparison UI documentation, independent hands-on confirmation of comparing parallel attempts.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed4/10

   Docs confirm agents can run in parallel (multiple agents across projects, multiple CLI agents for large tasks) and a central dashboard to monitor/orchestrate them, but nothing describes running multiple attempts at the SAME task and comparing outputs before choosing a winner — that specific 'compare-and-select' workflow is unevidenced. missing for 10: explicit multi-attempt/variant generation for a single task, a comparison UI or ranking mechanism, and any selection step among parallel attempts.

   • [claimed-docs] “Have multiple agents working in parallel, so larger tasks get tackled faster.”
   • [claimed-docs] “Orchestrate multiple autonomous agents working in parallel across independent projects.”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”

   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 Google Antigravity
   Codex~partialclaimed5/10

   Codex cloud supports starting tasks from external triggers (GitHub/GitLab issues & PRs, Linear issues, Slack messages) and running them in parallel isolated environments, which covers the 'triggers' half of the story, but there's no evidence of a true schedule/cron-based always-on agent that proactively maintains a repo without an external event. Missing for 10: explicit scheduled/cron execution, evidence of continuous unattended monitoring/maintenance loops, and independent confirmation these triggers reliably run autonomous fixes end-to-end.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”

   proof ↗⚑ flag

   Google Antigravity✓fullcommunity7/10

   First-party docs explicitly describe Scheduled Tasks with cron schedules that start and run agents autonomously in the background, plus scheduling messages to agents while away, parallel autonomous agent orchestration, and headless CLI mode for CI/trigger-based automation. However, there is no independent/hands-on corroboration of the scheduling feature itself, and community reports document serious reliability/safety incidents with autonomous execution (e.g., an agent deleting a whole drive via unattended terminal auto-execution), raising doubt about safely running such agents unattended. Missing for 10: independent verification that scheduled/cron-triggered agents work reliably in practice, and evidence that autonomous 'maintain and fix' runs don't require the same close supervision seen in incident reports.

   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “users can schedule messages to be sent to their agents while they’re away”
   • [claimed-docs] “Orchestrate multiple autonomous agents working in parallel across independent projects.”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [community] “Google Antigravity just deleted the contents of whole drive - came down to commanding a deletion of a 'directory with space in the name' wit…”

   proof ↗⚑ flag

Debugging

1. developerDebug issues and troubleshoot using natural-language queries

   weight 2 · round to Codex
   Codex~partialcommunity7/10

   Codex CLI docs show clear natural-language debugging workflows: exploring unfamiliar code, running local tools, passing error screenshots for context, and running dedicated code review that reports prioritized findings (codex-docs-8, codex-docs-9, codex-docs-10, codex-docs-12). However, community evidence shows mixed real-world reliability on agentic/coding tasks and no independent confirmation specifically validating debugging accuracy. Missing for 10: hands-on validation of debugging/troubleshooting accuracy, and independent case studies showing successful root-cause diagnosis via NL queries.

   • [claimed-docs] “Inspect code, make changes, run commands, and automate repeatable work without leaving your terminal.”
   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Pass an error screenshot, architecture diagram, or design reference with the first prompt, or paste an image into the interactive composer.”
   • [community] “Having used codex a fair bit I find it really struggles with … almost anything. However using the equivalent chat gpt model is fantastic.”
   • [community] “Often Claude Code Opus 4.6, on hard enough problems, can do the impression of acting fast without really making progress. Then you spin the …”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed6/10

   Antigravity's docs show natural-language code commands, autonomous operation across editor/terminal/browser, and subagents that can run tests and search codebases (docs-6,7,9,18,46), which collectively support debugging/troubleshooting via NL prompts, but there is no explicit documentation of a dedicated 'debug' workflow or troubleshooting examples, and community reports focus on stability/security issues rather than confirming debugging quality. Missing for 10: explicit debugging-specific documentation or examples, and independent hands-on validation that NL debugging queries work reliably.

   • [claimed-docs] “Google Antigravity's Editor view offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurab…”
   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents”

   proof ↗⚑ flag

Feature implementation

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

   weight 3 · round to Codex
   Codex✓fullclaimed8/10

   Codex explicitly supports starting work from a tracked issue (GitHub, GitLab, Linear) in cloud environments, running the task, inspecting the diff/summary, and opening a pull request when done, covering the full issue-to-PR loop. missing for 10: independent hands-on confirmation of a full issue-to-merged-PR workflow succeeding end-to-end, and detail on how issue context/acceptance criteria are actually parsed.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   Antigravity's docs describe autonomous coding agents that can edit files, run terminal commands, and operate across editor/terminal/browser, but there is no evidence of any issue-tracker (e.g., GitHub Issues) integration or an end-to-end workflow that ingests a tracked issue and produces a pull request. Missing for 10: issue-tracker ingestion, automated branch/PR creation, and any documented GitHub/GitLab PR workflow example.

   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”

   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 to Codex
   Codex✓fullcommunity8/10

   Codex CLI and cloud docs describe the core loop of natural-language task description leading to autonomous file inspection, editing, running local tools, and producing a diff/PR (codex-docs-30, codex-docs-9, codex-docs-6, codex-docs-5), and community commentary corroborates it does real multi-file edits ('it edits the files and I can use the proper tooling', 'shockingly good... no worse than average L3-L4 engs') alongside some negative UX complaints that don't dispute the core capability. Missing for 10: independent benchmark/case-study evidence specifically confirming complex multi-file refactors across large codebases, and some community reports of it 'struggling with almost anything' create mild quality tension without rising to a concrete dispute.

   • [claimed-docs] “Work against your local repository: Let Codex inspect files, make edits, and run the tools already installed on your machine.”
   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”
   • [community] “Codex is my favorite UX for anything as it edits the files and I can use the proper tooling to adjust and test stuff... However lately the l…”
   • [community] “Genuinely excited to try this out. I've started using Codex much more heavily in the past two months and honestly, it's been shockingly good…”
   • [community] “Having used codex a fair bit I find it really struggles with … almost anything. However using the equivalent chat gpt model is fantastic.”

   proof ↗⚑ flag

   Google Antigravity~partialcommunity7/10

   Docs describe the core loop clearly: natural-language commands drive an agent that autonomously edits code across the editor/terminal, with Projects spanning multiple folders/repos giving full codebase context and Artifacts showing diffs/plans for review (antigravity-docs-6,7,9,17,24,30,40). Community reports confirm it functions as a real coding-agent IDE (comm-1) but also describe hands-on quality issues with the agent harness and model reliability during actual implementation work (comm-8), so delivery is real but not consistently polished. Missing for 10: independent benchmark/case-study evidence of successful multi-file feature implementation, and resolution of reported harness/quality complaints.

   • [claimed-docs] “Google Antigravity's Editor view offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurab…”
   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “Planning Mode: The agent plans thoroughly before executing tasks... produces structured implementation plans called Artifacts”
   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “Build AI agents that autonomously read files, run commands, edit code, and more.”
   • [community] “I went ahead and downloaded it, it looks to be a VSCode fork very similar to Cursor, with support for Gemini 3 Pro, Claude Sonnet 4.5, and G…”
   • [community] “It's not even good, honestly. I was using it for couple weeks before dropping that 2 months ago. The model was not good and slow, the harnes…”

   proof ↗⚑ flag

Maintenance automation

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

   weight 3 · round drawn
   Codex~partialcommunity6/10

   Codex CLI/cloud docs describe a general-purpose coding agent that can inspect code, edit files, run local dev tools, automate repeatable work, and review diffs before PRs — capabilities broad enough to plausibly cover writing tests, fixing lint issues, resolving conflicts, and updating dependencies (codex-docs-8, codex-docs-9, codex-docs-30, codex-docs-41). However, none of the docs explicitly name test-writing, lint-fixing, merge-conflict resolution, or dependency updates as supported workflows, and community feedback is mixed on real-world reliability for complex agentic tasks (codex-comm-3, codex-comm-13). missing for 10: explicit documentation/examples of test generation, lint-fix automation, merge-conflict resolution, and dependency-update workflows, plus hands-on confirmation these specific tasks succeed.

   • [claimed-docs] “Inspect code, make changes, run commands, and automate repeatable work without leaving your terminal.”
   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Work against your local repository: Let Codex inspect files, make edits, and run the tools already installed on your machine.”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [community] “Codex is my favorite UX for anything as it edits the files and I can use the proper tooling to adjust and test stuff... However lately the l…”
   • [community] “Having used codex a fair bit I find it really struggles with … almost anything. However using the equivalent chat gpt model is fantastic.”

   proof ↗⚑ flag

   Google Antigravity~partialcommunity6/10

   Antigravity's docs describe general-purpose coding agents/subagents that can run tests, edit code, and operate across editor/terminal/browser (docs-18, docs-46, docs-40, docs-7), which implicitly covers writing tests and dependency/code edits, but there is no explicit documentation calling out lint-error fixing, merge-conflict resolution, or dependency updates as named capabilities. Community evidence is mixed on general quality/reliability but does not concretely refute these specific tasks. Missing for 10: explicit first-party documentation or hands-on examples of lint-fixing, merge-conflict resolution, and dependency-update workflows specifically.

   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents”
   • [claimed-docs] “Build AI agents that autonomously read files, run commands, edit code, and more.”
   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “The Agent SDK gives you the same tools, agent loop, and context management that power Google Antigravity, programmable in Python.”
   • [community] “It's not even good, honestly. I was using it for couple weeks before dropping that 2 months ago. The model was not good and slow, the harnes…”

   proof ↗⚑ flag

Multimodal generation

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

   weight 2 · round drawn
   Codex~partialclaimed4/10

   Codex supports passing images (error screenshots, architecture diagrams, design references) into prompts, which is a partial building block for generating apps from a sketch/image, but there's no evidence of dedicated PDF-to-app workflows, multi-page design ingestion, or documented end-to-end 'sketch/image to working app' generation feature. missing for 10: explicit PDF design ingestion, dedicated image/design-to-app pipeline or template, independent hands-on demonstration of generating a full app from a design artifact.

   • [claimed-docs] “Pass an error screenshot, architecture diagram, or design reference with the first prompt, or paste an image into the interactive composer.”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed4/10

   Antigravity supports passing images, PDFs and other multimedia attachments to the agent as part of prompts (docs-15, docs-32), which implies it could take a sketch/image/PDF as design input for code generation, but there is no explicit documentation or example of a 'sketch-to-app' or 'design-to-code' workflow, nor any hands-on report of this being used successfully. missing for 10: dedicated design-to-app feature/workflow documentation, an example or case study of generating an app from an image/PDF, and independent verification that this works in practice.

   • [claimed-docs] “Pass rich multimedia file attachments (images, videos, audio, and documents) to the agent alongside textual instruction prompt lists.”
   • [claimed-docs] “External files such as Google Drive links, PDFs, and Office documents now appear in their own Documents section in the sidebar above Artifac…”

   proof ↗⚑ flag

Codebase mapping

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

   weight 3 · round drawn
   Codex~partialclaimed6/10

   Codex CLI docs explicitly mention exploring unfamiliar code and planning changes within a repository, and it can inspect code, run local dev tools, and review diffs/commits — supporting codebase orientation. However, there's no dedicated codebase-mapping/visualization feature, no evidence of dependency-graph or architecture-summary generation, and community feedback focuses on agentic task execution rather than comprehension aids. Missing for 10: dedicated codebase-map/architecture-overview feature, independent hands-on evidence of effectively onboarding to unfamiliar large codebases, and richer navigation/search tooling beyond terminal chat resume.

   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Inspect code, make changes, run commands, and automate repeatable work without leaving your terminal.”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Reopen a recent chat from the current repository, or search across local chats when you need to return to older work.”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed6/10

   Antigravity provides contextual codebase understanding indirectly: Projects give agents full context across multiple folders/repos, subagents can perform 'extensive codebase searches', and Artifacts can include architecture diagrams and implementation plans that map out how a change fits into the codebase. However, there's no dedicated codebase-mapping/explanation feature, and no independent/hands-on evidence confirming how well the agent actually explains codebase structure. Missing for 10: a first-class 'explain/visualize codebase architecture' feature, independent hands-on validation of comprehension quality on real repos.

   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “Agents work within Projects, which define the boundaries of the folders and repositories they can access.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents”
   • [claimed-docs] “Google Antigravity's Editor view offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurab…”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   Codex~partialclaimed5/10

   Codex CLI docs explicitly state it can be started in a repository 'to explore unfamiliar code, plan a change, edit files, and run your local development tools' (codex-docs-9), implying the agent autonomously navigates the codebase rather than requiring manual file selection, and codex-gh-1 confirms it runs as an autonomous coding agent locally. However, there's no detailed documentation of how it builds a whole-codebase map/summary, no explicit 'explain codebase' feature, and no independent hands-on evidence confirming this works well on large unfamiliar repos. Missing for 10: dedicated codebase-mapping/summarization feature documentation, evidence of handling very large repos, and independent user reports validating this specific capability.

   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed5/10

   Docs indicate agents automatically get full-project context (docs-17, docs-35) and can delegate to subagents that perform 'extensive codebase searches' (docs-18/46), suggesting the agent can explore an unfamiliar repo without manual file selection. However, there is no explicit feature or example describing whole-codebase mapping/explanation, and no independent/hands-on evidence confirming this works well in practice. missing for 10: a dedicated 'explain codebase' or repo-mapping feature description, and independent verification of this on an unfamiliar large codebase.

   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “Agents work within Projects, which define the boundaries of the folders and repositories they can access.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents”

   proof ↗⚑ flag

Context management

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

   weight 2 · round to Codex
   Codex~partialclaimed3/10

   Codex CLI supports `codex resume` to reopen or search past local chats in a repository, giving a limited form of session recall, but this requires manual user action rather than automatic memory building/recall across sessions. Missing for 10: evidence of automatic persistent memory (learned facts, preferences, or context) that Codex builds unprompted and recalls without explicit resume/search commands, and any cross-session synthesis beyond raw chat transcripts.

   • [claimed-docs] “Reopen a recent chat from the current repository, or search across local chats when you need to return to older work.”
   • [claimed-docs] “`codex resume`: Reopen a recent chat from the current repository, or search across local chats when you need to return to older work.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   The evidence describes Projects, Rules, Artifacts, and context management, but none of these describe an automatic memory system that builds and recalls information across sessions without user re-specification; Rules are explicitly manual, and Projects only scope folders/permissions, not persistent learned memory. No documentation or community evidence confirms automatic cross-session memory recall.

   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “At the rule level you can define how a rule should be activated: Manual... Always On... Model Decision... Glob”
   • [claimed-docs] “Agents work within Projects, which define the boundaries of the folders and repositories they can access.”
   • [claimed-docs] “Rules are manually defined constraints for the Agent to follow, at both the local and global levels.”

   proof ↗⚑ flag

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

   weight 2 · round to Google Antigravity
   Codex—none0/10

   No evidence in the pack describes Codex supporting multiple project directories or repositories being combined in a single session/context; documentation focuses on single-repository sessions, cloud tasks, and per-repository setup steps.

   ⚑ flag

   Google Antigravity✓fullclaimed8/10

   Docs explicitly state Projects can span multiple folders (e.g., a frontend and backend repo) giving agents full codebase context, with Projects defining folder/repo access boundaries and worktree support for isolated background folders. Missing for 10: independent/hands-on corroboration of multi-folder session use in practice.

   • [claimed-docs] “Group your conversations into Projects, which can span multiple folders and support custom settings and scoped permissions.”
   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “Agents work within Projects, which define the boundaries of the folders and repositories they can access.”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”

   proof ↗⚑ flag

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

   weight 3 · round to Google Antigravity
   Codex—none0/10

   The evidence pack covers Codex's CLI, cloud, MCP, and review features but contains no mention of a project-level instructions/config file (e.g., AGENTS.md or similar) for setting coding standards or conventions the agent should follow. This is a plausible and common capability for coding agents, but nothing in the pack documents or demonstrates it.

   ⚑ flag

   Google Antigravity✓fullclaimed7/10

   Antigravity supports Rules (manually defined constraints for the agent at local and global levels, with activation modes like Always On/Glob) which serve as a project instructions file for coding standards and conventions, and Projects scope these settings per folder/repo. missing for 10: no independent/hands-on confirmation of rules file format or behavior, and no evidence of a specific standardized file name (e.g. AGENTS.md-equivalent) or examples of it being used in practice.

   • [claimed-docs] “At the rule level you can define how a rule should be activated: Manual... Always On... Model Decision... Glob”
   • [claimed-docs] “Rules are manually defined constraints for the Agent to follow, at both the local and global levels.”
   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “Agents work within Projects, which define the boundaries of the folders and repositories they can access.”

   proof ↗⚑ flag

Issue diagnosis

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

   weight 3 · round to Codex
   Codex✓fullclaimed7/10

   Codex CLI docs explicitly describe exploring unfamiliar code and running local dev tools to investigate issues, passing error screenshots for context, delegating focused investigation to subagents, and running dedicated reviews against uncommitted changes/commits/base branches to verify fixes before committing — covering reproduce, narrow-down, and verify steps. Missing for 10: no explicit 'reproduce a bug' walkthrough or first-hand/independent account of successfully diagnosing and fixing a real bug end-to-end with Codex.

   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Pass an error screenshot, architecture diagram, or design reference with the first prompt, or paste an image into the interactive composer.”
   • [claimed-docs] “Ask Codex to delegate focused work to specialized agents, then bring their findings back into the main terminal session.”
   • [claimed-docs] “Work against your local repository: Let Codex inspect files, make edits, and run the tools already installed on your machine.”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”

   proof ↗⚑ flag

   Google Antigravity~partialcommunity6/10

   Antigravity's agents can run terminal commands and browser sessions, delegate to subagents that run tests or search the codebase (docs-18, docs-46, docs-7), and produce Artifacts with diffs, plans and browser recordings that could serve as reproduction/verification evidence (docs-30, docs-51). Headless/CI mode (docs-50) also supports automated verification loops. However there is no explicit documented workflow for issue reproduction or root-cause narrowing, and community reports show real-world reliability problems (deleted directories, exfiltration bugs) rather than confirmation that debugging workflows work well. Missing for 10: a dedicated debugging/root-cause-analysis feature, explicit test-verification-of-fix workflow, and independent hands-on validation that this works well in practice.

   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [claimed-docs] “An Artifact is a structured deliverable created by the agent to accomplish its task and communicate its progress and thinking to the human u…”
   • [community] “Google Antigravity just deleted the contents of whole drive - came down to commanding a deletion of a 'directory with space in the name' wit…”

   proof ↗⚑ flag

Marketplace

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

   weight 1 · round to Google Antigravity
   Codex✓fullclaimed7/10

   Codex CLI docs explicitly describe packaging repeatable instructions as "skills" and adding plugins to connect Codex to team tools/data from the CLI, directly matching the custom-skills story. Missing for 10: independent hands-on validation of skill creation/usage, and deeper documentation on skill authoring format/lifecycle beyond a single mention.

   • [claimed-docs] “Package repeatable instructions as skills, then add plugins to connect Codex to your team's tools and data without leaving the CLI.”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed8/10

   Antigravity has a dedicated Skills system: SKILL.md-based reusable packages of knowledge/instructions the agent follows for specific tasks, creatable/downloadable and accessible via slash commands, plus composable with plugins that bundle skills, rules, MCP servers, and hooks. This is documented across product and docs pages consistently, though no independent/community hands-on verification of custom skills specifically was found. Missing for 10: independent/hands-on corroboration of custom skill creation working in practice, and a marketplace/registry of shareable skills.

   • [claimed-docs] “Create or download fully customizable skills to further your agent’s autonomy and transform how you get work done.”
   • [claimed-docs] “A skill is a folder containing a `SKILL.md` file with instructions that the agent can follow when working on specific tasks.”
   • [claimed-docs] “Skills are reusable packages of knowledge that extend what the agent can do.”
   • [claimed-docs] “Access plugins, MCP, skills, and hooks configurations instantly via slash commands, quickly enhancing your workflow.”
   • [claimed-docs] “Layer custom Python callables, Model Context Protocol (MCP) servers, and reusable agent skills over our built-in filesystem and terminal too…”
   • [claimed-docs] “Plugins are namespaced bundles that allow you to extend Antigravity’s capabilities by grouping skills, rules, MCP servers, and hooks into a …”

   proof ↗⚑ flag

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

   weight 1 · round to Codex
   Codex~partialclaimed6/10

   Codex documents integration points for third-party ecosystem tools — triggering work from GitHub, GitLab, Linear, and Slack (partner platforms), and connecting to third-party MCP servers, plugins, and skills that give access to tools like Figma or a browser — which supports embedding partner-built capabilities into engineering workflows. However, the evidence is framed around Codex consuming tools/data sources rather than a curated marketplace of partner-built 'agent apps,' and there's no independent case study of a partner agent integration working end-to-end. Missing for 10: evidence of a partner/agent-app marketplace or certified third-party agent integrations, and independent verification of such integrations working in practice.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Package repeatable instructions as skills, then add plugins to connect Codex to your team's tools and data without leaving the CLI.”
   • [claimed-docs] “Use it to give ChatGPT or Codex access to third-party documentation, or to let it interact with developer tools like your browser or Figma.”
   • [claimed-docs] “Connect external tools with MCP — codex mcp: Add local or remote MCP servers, authenticate when needed, and inspect the tools available to t…”
   • [claimed-docs] “Use skills and plugins: Package repeatable instructions as skills, then add plugins to connect Codex to your team's tools and data without l…”
   • [claimed-docs] “Model Context Protocol (MCP) connects models to tools and context. Use it to give ChatGPT or Codex access to third-party documentation, or t…”

   proof ↗⚑ flag

   Google Antigravity!disputedcontradicted4/10

   Vendor docs describe an extensibility layer (MCP servers, plugins, skills, hooks) that in principle lets teams plug in third-party building blocks (docs-14, docs-28, docs-12), suggesting an ecosystem for integrating outside agent capabilities. However, hands-on community reports directly contradict the notion of freely integrating partner-built agent apps: using a third-party agent ('Pi agent') alongside Antigravity triggered a Google account ban under Antigravity's TOS restricting 3rd-party usage, and users discovered unofficial vs official extensions causing confusion (comm-17, comm-18). Missing for 10: an official partner/marketplace program for third-party agent apps, clear TOS allowance for such integrations, and independent confirmation that such integrations work without account risk.

   • [claimed-docs] “Layer custom Python callables, Model Context Protocol (MCP) servers, and reusable agent skills over our built-in filesystem and terminal too…”
   • [claimed-docs] “Plugins are namespaced bundles that allow you to extend Antigravity’s capabilities by grouping skills, rules, MCP servers, and hooks into a …”
   • [claimed-docs] “Access plugins, MCP, skills, and hooks configurations instantly via slash commands, quickly enhancing your workflow.”
   • [community] “Google Antigravity TOS: 3rd party usage can get Google account suspended. My friend got a ban by using Pi agent with Antigravity. They un-ba…”
   • [community] “The VSCode Antigravity extension I was using turns out to be a 3rd-party one. I found out only today that there's an official extension too,…”

   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 drawn
   Codex—none0/10

   Codex documents repo-level cloud environments, RBAC, and MCP connections to team tools, but no evidence describes a shared 'workspace' feature that unifies docs and repos into a common source of truth for a team; this is a plausible ask for an engineering tool but Codex's evidence only covers per-task cloud environments and repo configuration, not a persistent shared knowledge/workspace layer.

   • [claimed-docs] “Configure the dependencies, tools, variables, and setup steps each repository needs.”
   • [claimed-docs] “Role-based access control (RBAC) lets you decide who can do what across your organization and projects—both through the API and in the Dashb…”
   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   Antigravity's 'Projects' concept groups folders/repos for a single agent session's context (docs-5, docs-17, docs-35, docs-38) and can surface Docs/Drive links (docs-32), but there is no evidence of a multi-user, team-shared workspace or collaborative source-of-truth that an engineering-lead could set up for a whole team — Projects appear to be individually scoped, local constructs rather than shared team assets.

   • [claimed-docs] “Group your conversations into Projects, which can span multiple folders and support custom settings and scoped permissions.”
   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “Agents work within Projects, which define the boundaries of the folders and repositories they can access.”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [claimed-docs] “External files such as Google Drive links, PDFs, and Office documents now appear in their own Documents section in the sidebar above Artifac…”

   proof ↗⚑ flag

Tool integration

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

   weight 3 · round to Codex
   Codex~partialclaimed6/10

   Codex explicitly supports starting work from Slack (and GitHub/GitLab/Linear) and lets users add local or remote MCP servers to connect to third-party tools/docs (e.g. Figma, browser), giving a generic mechanism to extend context to workflow tools. However, there is no explicit documentation of native Jira or Google Drive connectors—only Slack is named among the story's specific tools, with Jira/Google Drive requiring the generic (and for one variant, deprecated/experimental) MCP server pathway. Missing for 10: named Jira integration, named Google Drive integration, and confirmation that the current (non-deprecated) MCP mechanism is broadly used for these specific SaaS tools.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Add local or remote MCP servers, authenticate when needed, and inspect the tools available to the current session before Codex uses them.”
   • [claimed-docs] “Package repeatable instructions as skills, then add plugins to connect Codex to your team's tools and data without leaving the CLI.”
   • [claimed-docs] “Use it to give ChatGPT or Codex access to third-party documentation, or to let it interact with developer tools like your browser or Figma.”
   • [claimed-docs] “Model Context Protocol (MCP) connects models to tools and context. Use it to give ChatGPT or Codex access to third-party documentation, or t…”
   • [claimed-docs] “Connect external tools with MCP — codex mcp: Add local or remote MCP servers, authenticate when needed, and inspect the tools available to t…”
   • [github] “Codex MCP Server Interface [experimental]: a JSON-RPC API that runs over the Model Context Protocol (MCP) transport to control a local Codex…”
   • [claimed-docs] “codex mcp-server is deprecated. Use the Codex app server instead. ... This page documents the deprecated command for existing integrations. …”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed5/10

   Antigravity documents generic MCP support for connecting to 'local developer tools, databases, file parsers, and external remote APIs' and explicitly shows Google Drive links/files appearing in its sidebar Documents section, giving a plausible path to hook in workflow tools. However, there is no explicit documentation of Jira or Slack connectors/integrations, and no first-party or community evidence of anyone actually wiring these specific tools in via MCP. Missing for 10: explicit Jira/Slack connector docs or MCP server examples, and independent confirmation of successful workflow-tool integrations beyond Drive.

   • [claimed-docs] “MCP lets Antigravity fetch structured context directly or execute safe actions on your behalf when needed.”
   • [claimed-docs] “lets AI agents and editors securely connect to local developer tools, databases, file parsers, and external remote APIs”
   • [claimed-docs] “External files such as Google Drive links, PDFs, and Office documents now appear in their own Documents section in the sidebar above Artifac…”
   • [claimed-docs] “Layer custom Python callables, Model Context Protocol (MCP) servers, and reusable agent skills over our built-in filesystem and terminal too…”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex✓fullclaimed8/10

   First-party docs explicitly state Codex cloud tasks can be started from GitHub pull requests, GitLab merge requests/issues, Linear issues, or Slack channels/threads, matching the story directly. Missing for 10: independent/hands-on verification of these specific integrations working in practice (community evidence covers CLI/app UX but not the GitHub/GitLab/Linear/Slack kickoff flows specifically).

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   No evidence that Antigravity supports kicking off agent tasks from GitHub, GitLab, Linear, or Slack; documentation covers IDE, CLI, SDK, scheduled tasks, and MCP but no mention of triggers from these external issue-tracker/chat platforms.

   ⚑ flag

Cross device continuity

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

   weight 2 · round to Codex
   Codex✓fullclaimed8/10

   Codex supports starting tasks in the cloud from web/GitHub/GitLab/Linear/Slack, working in parallel cloud environments, and later resuming or continuing work from the CLI via 'codex cloud' (browse active/completed chats, submit/apply results) or 'codex resume' to reopen local chats, plus a shared MCP config across ChatGPT desktop, CLI, and IDE extension enabling cross-client continuity. missing for 10: independent hands-on confirmation of seamless state sync across devices/browsers, and no explicit mention of resuming a cloud-started task from a different physical device's browser session.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Start and review work from the web or Codex CLI.”
   • [claimed-docs] “Move work to Codex cloud — codex cloud: Browse active and completed chats, submit work to a configured environment, and apply the result to …”
   • [claimed-docs] “`codex resume`: Reopen a recent chat from the current repository, or search across local chats when you need to return to older work.”
   • [claimed-docs] “The ChatGPT desktop app, Codex CLI, and IDE extension share this configuration. Once you configure your MCP servers, you can switch among th…”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed7/10

   Antigravity Remote Control explicitly lets users securely connect to and drive their desktop Antigravity sessions from any web browser, directly enabling continuing a task started on one device from another device/browser, and scheduled/background tasks further support async continuation across sessions. Missing for 10: independent hands-on verification of cross-device continuity, details on session/state sync fidelity, and any community confirmation of this specific feature working in practice.

   • [claimed-docs] “Antigravity Remote Control allows you to securely connect to and drive your Antigravity 2.0 desktop sessions running across your machines fr…”
   • [claimed-docs] “users can schedule messages to be sent to their agents while they’re away”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”

   proof ↗⚑ flag

Ide integration

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

   weight 1 · round drawn
   Codex—none0/10

   Evidence shows Codex's IDE extension explicitly targets VS Code, Cursor, and Windsurf (codex-gh-2), with no mention of JetBrains IDEs, interactive diff viewing within an IDE, or a 'share selected code as context' feature. The axis (IDE integration) is clearly applicable to Codex as a coding agent, but JetBrains-specific support and the described interactive-diff/context-sharing workflow are simply absent from the evidence pack.

   • [github] “If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   Antigravity is documented as a standalone VSCode-fork IDE with its own Editor view, Artifacts diff viewer, and CLI/SDK — there is no mention anywhere in the docs, changelog, or community threads of a JetBrains plugin or JetBrains-specific integration for diffs or context sharing.

   • [claimed-docs] “Google Antigravity's Editor view offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurab…”
   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “Added a "Hide Whitespace Changes" option to the Review Changes overflow menu and file diff viewers to filter out whitespace-only edits.”
   • [claimed-docs] “Code and data artifacts like SQL and JSONL files now open in a virtualized viewer with syntax highlighting and line numbers”
   • [community] “I went ahead and downloaded it, it looks to be a VSCode fork very similar to Cursor, with support for Gemini 3 Pro, Claude Sonnet 4.5, and G…”

   proof ↗⚑ flag

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

   weight 3 · round to Codex
   Codex✓fullcommunity8/10

   Codex explicitly offers an IDE extension for VS Code, Cursor, and Windsurf, plus a CLI usable within the terminal in your repo, both providing contextual chat/help with the codebase (edit files, run commands, review diffs). Community evidence confirms real-world usage of Codex CLI/app for editing and testing files in context, though some note UX friction compared to competitors. Missing for 10: deeper first-party documentation/screenshots of the IDE extension's chat UI specifically, and stronger independent hands-on corroboration of in-IDE chat quality.

   • [github] “If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.”
   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Inspect code, make changes, run commands, and automate repeatable work without leaving your terminal.”
   • [community] “Codex is my favorite UX for anything as it edits the files and I can use the proper tooling to adjust and test stuff... However lately the l…”

   proof ↗⚑ flag

   Google Antigravity✓fullcommunity7/10

   Antigravity is a VSCode-fork IDE with an editor view offering tab autocompletion, natural language code commands, and a context-aware conversational agent, confirmed by community hands-on reports of using it like Cursor. This directly supports in-IDE chat for contextual help. missing for 10: independent review specifically praising chat UX/quality (community notes mixed quality/performance complaints), and no detailed walkthrough of the chat interface itself beyond high-level docs.

   • [claimed-docs] “Google Antigravity's Editor view offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurab…”
   • [claimed-docs] “offers tab autocompletion, natural language code commands, and a configurable, and context-aware configurable agent”
   • [community] “I went ahead and downloaded it, it looks to be a VSCode fork very similar to Cursor, with support for Gemini 3 Pro, Claude Sonnet 4.5, and G…”
   • [claimed-docs] “Users can select which reasoning model they want to use within the model selector drop-down under the conversation prompt box”

   proof ↗⚑ flag

Session management

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

   weight 2 · round to Google Antigravity
   Codex~partialcommunity5/10

   Codex ships a desktop app ("codex app"/Codex App page) and documents parallel task execution plus diff/summary inspection before merging, suggesting the underlying pieces exist, but the evidence never shows the desktop app UI actually presenting a visual diff viewer or multiple sessions arranged side by side. Community notes even flag basic desktop-app reliability issues (stuck on 'Loading projects...', Mac-only availability). Missing for 10: concrete documentation/screenshots of the desktop app's diff viewer, explicit multi-session/side-by-side UI description, and independent confirmation it works smoothly.

   • [github] “If you want the desktop app experience, run <code>codex app</code> or visit the Codex App page.”
   • [github] “If you want the desktop app experience, run <code>codex app</code> or visit <a href="https://chatgpt.com/codex?app-landing-page=true">the Co…”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [community] “Genuinely excited to try this out. I've started using Codex much more heavily in the past two months and honestly, it's been shockingly good…”
   • [community] “Mac only. Again. Apple is great but this is OpenAI devs showing their disconnect from the mainstream.”

   proof ↗⚑ flag

   Google Antigravity✓fullcommunity8/10

   Antigravity's desktop app (confirmed as a VSCode-style editor) ships a dedicated 'Review Changes' diff viewer with whitespace filtering and syntax-highlighted artifacts (antigravity-docs-33, -34, -30), plus explicit support for running multiple agents/sessions in parallel across independent projects and worktrees from one command center (antigravity-docs-1, -37, -38, -10). Missing for 10: independent hands-on confirmation of the side-by-side multi-session UI specifically (community evidence mostly discusses general bugs/instability rather than this feature directly).

   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “Added a "Hide Whitespace Changes" option to the Review Changes overflow menu and file diff viewers to filter out whitespace-only edits.”
   • [claimed-docs] “Code and data artifacts like SQL and JSONL files now open in a virtualized viewer with syntax highlighting and line numbers”
   • [claimed-docs] “Planning Mode: The agent plans thoroughly before executing tasks... produces structured implementation plans called Artifacts”
   • [claimed-docs] “The agent always halts and requests your explicit approval before proceeding with proposed changes.”
   • [claimed-docs] “Orchestrate multiple autonomous agents working in parallel across independent projects.”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [community] “I went ahead and downloaded it, it looks to be a VSCode fork very similar to Cursor, with support for Gemini 3 Pro, Claude Sonnet 4.5, and G…”

   proof ↗⚑ flag

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

   weight 2 · round to Google Antigravity
   Codex✓fullcommunity7/10

   Codex documents cloud parallel task execution across multiple repos/environments (codex-docs-1,3,6), a web/CLI dashboard to browse active and completed chats and apply results locally (codex-docs-15), and resuming/searching across sessions (codex-docs-11,24), which together support managing multiple concurrent agent sessions from a unified interface. However, evidence is vendor-documentation only with no independent hands-on confirmation of a true 'unified workspace' UX for an engineering-lead managing many sessions simultaneously, and some community comments note UX rough edges (codex-comm-9,18). Missing for 10: independent/hands-on verification of multi-session management at scale, and clearer detail on cross-session visibility/coordination for a lead overseeing a team's agents.

   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Run tasks in parallel without tying up your local machine.”
   • [claimed-docs] “Delegate a longer task and return when it is ready.”
   • [claimed-docs] “Browse active and completed chats, submit work to a configured environment, and apply the result to your local repository from the terminal.”
   • [claimed-docs] “Reopen a recent chat from the current repository, or search across local chats when you need to return to older work.”
   • [claimed-docs] “`codex resume`: Reopen a recent chat from the current repository, or search across local chats when you need to return to older work.”
   • [community] “I wish Codex App was open source. I like it, but there are always a bunch of little paper cuts that, if you were using codex cli, you could …”

   proof ↗⚑ flag

   Google Antigravity✓fullcommunity8/10

   Antigravity's docs describe a unified 'command center' (antigravity-docs-37) that lets a lead orchestrate multiple autonomous agents in parallel across projects (antigravity-docs-1, antigravity-docs-10), grouped into Projects spanning folders/repos with scoped permissions (antigravity-docs-5, antigravity-docs-17, antigravity-docs-35), plus worktree isolation (antigravity-docs-38), scheduled/background tasks (antigravity-docs-2, antigravity-docs-39), subagent delegation (antigravity-docs-18/19), and even remote browser-based control of running sessions (antigravity-docs-26). This directly matches the engineering-lead's need to manage many concurrent agent sessions from one place. Missing for 10: independent verification of managing many simultaneous sessions at scale, and community reports note real stability/reliability issues (antigravity-comm-6, antigravity-comm-8, antigravity-comm-9) that temper confidence though they don't specifically contradict the multi-session orchestration claim.

   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”
   • [claimed-docs] “Orchestrate multiple autonomous agents working in parallel across independent projects.”
   • [claimed-docs] “Have multiple agents working in parallel, so larger tasks get tackled faster.”
   • [claimed-docs] “Group your conversations into Projects, which can span multiple folders and support custom settings and scoped permissions.”
   • [claimed-docs] “a project can work with one folder or multiple folders (e.g., a frontend and a backend repo), providing your agents with all of the context …”
   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [claimed-docs] “Automate routine checks with Scheduled Tasks, simply define a cron schedule and the agents start and run autonomously in the background.”
   • [claimed-docs] “Antigravity Remote Control allows you to securely connect to and drive your Antigravity 2.0 desktop sessions running across your machines fr…”
   • [community] “Google made its lack of interest in Antigravity IDE obvious from very early. Updates were few and far between and app-breaking bugs stuck ar…”
   • [community] “It's not even good, honestly. I was using it for couple weeks before dropping that 2 months ago. The model was not good and slow, the harnes…”

   proof ↗⚑ flag

Terminal workflow

1. developerRun a coding agent locally from my terminal

   weight 3 · round to Codex
   Codex✓fullcommunity9/10

   Codex CLI is explicitly documented as a coding agent that runs locally in the terminal, with npm/standalone install, working against the local repository, editing files, running commands, and offering interactive TUI plus non-interactive exec mode — well corroborated by first-party docs and GitHub README, with community usage discussion confirming real-world use. Missing for 10: independent hands-on verification specifically of pure local terminal usage (most community commentary discusses model quality/UX rather than the local-run mechanics) and some caveats about performance/limits reported by users.

   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”
   • [github] “npm install -g @openai/codex”
   • [claimed-docs] “Inspect code, make changes, run commands, and automate repeatable work without leaving your terminal.”
   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Work against your local repository: Let Codex inspect files, make edits, and run the tools already installed on your machine.”
   • [claimed-docs] “Compose with scripts and CI: Use Codex interactively or call codex exec from repeatable workflows and pipelines.”
   • [claimed-docs] “Install the Codex CLI with the standalone installer for macOS and Linux.”
   • [community] “Codex is my favorite UX for anything as it edits the files and I can use the proper tooling to adjust and test stuff... However lately the l…”
   • [community] “Genuinely excited to try this out. I've started using Codex much more heavily in the past two months and honestly, it's been shockingly good…”

   proof ↗⚑ flag

   Google Antigravity✓fullprobed8/10

   Google Antigravity ships an official CLI product (antigravity-cli) with terminal-native features like slash commands, headless/non-interactive mode for scripting, sandboxing, vim-mode editing, and config management, explicitly designed to run agents locally from the terminal, and a community comment confirms using 'Antigravity CLI with vscode' works fine. Missing for 10: deeper independent hands-on reviews specifically of the CLI (most community feedback focuses on the IDE, not the terminal tool) and no third-party benchmarks of terminal performance/reliability.

   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “Have multiple agents working in parallel, so larger tasks get tackled faster.”
   • [claimed-docs] “Navigate your entire workflow via standard terminal shortcuts: adjust permissions, themes, and preferences via /config and type /keybindings…”
   • [claimed-docs] “Access plugins, MCP, skills, and hooks configurations instantly via slash commands, quickly enhancing your workflow.”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [claimed-docs] “Sensitive files like ~/.ssh and .env are blocked, anything not explicitly mounted is invisible inside the sandbox”
   • [claimed-docs] “Vim editor mode replaces the editing model in every multi-line input surface of the CLI”
   • [probe] “official CLI documented at https://antigravity.google/product/antigravity-cli”
   • [community] “I much prefer using Gemini CLI in combination with vscode. It works like a charm. Now, I'll do the same with Antigravity CLI and vscode. It …”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex✓fullclaimed8/10

   Docs explicitly describe running 'a non-interactive command in a repeatable workflow' and automating repeatable work without leaving the terminal, plus support for submitting work to configured environments from scripts (codex exec-style usage implied). Missing for 10: independent hands-on confirmation of non-interactive/CI usage and detailed exit-code/output-format documentation for scripting.

   • [claimed-docs] “Run a non-interactive command in a repeatable workflow.”
   • [claimed-docs] “Inspect code, make changes, run commands, and automate repeatable work without leaving your terminal.”
   • [claimed-docs] “Browse active and completed chats, submit work to a configured environment, and apply the result to your local repository from the terminal.”
   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”

   proof ↗⚑ flag

   Google Antigravity✓fullclaimed7/10

   Official docs explicitly describe a headless mode: 'Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output,' directly matching the workflow-automation story. Missing for 10: independent/hands-on confirmation of headless CI usage and details on machine-readable output format/exit codes.

   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [claimed-docs] “Edit, orchestrate, and build all in natural language. Tell your agents what you need, and they’ll work on getting it done.”
   • [claimed-docs] “Create or download fully customizable skills to further your agent’s autonomy and transform how you get work done.”

   proof ↗⚑ flag

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

   weight 2 · round to Google Antigravity
   Codex~partialcommunity3/10

   Codex ships rich CLI/UI-only capabilities (cloud tasks, resume/review, skills, plugins, MCP client integration) with no evidence these are exposed via a dedicated Codex API, and the general OpenAI API (RBAC, Responses API) is not shown to cover Codex-specific workflows; community evidence even confirms the latest gpt-5.3-codex model 'isn't available on the API yet,' a documented parity gap. Missing for 10: documented API endpoints for cloud task delegation, chat/session resume, MCP tool orchestration, and confirmation that current models/features are API-accessible at parity with CLI/UI.

   • [github] “You can also use Codex with an API key, but this requires additional setup.”
   • [community] “gpt-5.3-codex isn't available on the API yet — 'We are working to safely enable API access soon.'”
   • [claimed-docs] “Role-based access control (RBAC) lets you decide who can do what across your organization and projects—both through the API and in the Dashb…”
   • [claimed-docs] “Create a model response — request/response reference with runnable code samples selectable per language: HTTP, Python, TypeScript, Go, Ruby,…”
   • [claimed-docs] “codex mcp-server is deprecated. Use the Codex app server instead. ... This page documents the deprecated command for existing integrations. …”

   proof ↗⚑ flag

   Google Antigravity~partialprobed4/10

   Antigravity offers an Agent SDK (Python programmable) and a headless/non-interactive CLI mode for scripting agent tasks, plugins, MCP, and hooks, suggesting substantial programmatic access to agent capabilities. However, there is no documented public REST/HTTP API or OpenAPI spec (probe explicitly found all openapi.json candidate paths 404'd), and no evidence that UI-only features like Remote Control, Editor tab-autocompletion, artifact review UI, or scheduled task UI are fully exposed via API parity. missing for 10: a documented public API/OpenAPI spec, confirmation that all UI features (remote control, artifact review, scheduling UI) have API equivalents, and independent verification of API-UI parity.

   • [claimed-docs] “The Agent SDK gives you the same tools, agent loop, and context management that power Google Antigravity, programmable in Python.”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [claimed-docs] “Layer custom Python callables, Model Context Protocol (MCP) servers, and reusable agent skills over our built-in filesystem and terminal too…”
   • [probe] “PROBE openapi: all candidate paths 404 (https://antigravity.google/openapi.json, https://antigravity.google/swagger.json, https://antigravit…”

   proof ↗⚑ flag

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

   weight 3 · round drawn
   Codex—none0/10

   No evidence of any data export feature or open-format export mechanism for chat history, project data, or configurations; Codex works with local files/git repos but there's no documented export/portability capability for user data (e.g., conversation history, settings) to leave the platform. Missing for 10: any documented data export tool, open-format export (JSON/Markdown dump), or data portability statement.

   ⚑ flag

   Google Antigravity—none0/10

   No evidence in the pack mentions data export, open-format portability, or account/data deletion features for Antigravity; docs cover projects, agents, artifacts, and CLI but never data portability or export-and-leave capability.

   ⚑ flag

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

   weight 2 · round to Codex
   Codex~partialcommunity4/10

   The Codex CLI source lives in a public GitHub repo (openai/codex) and a community comment implies its openness lets users 'diagnose and file an issue' the way they can't with the closed-source Codex App, suggesting at least the CLI's code is publicly viewable. However, no evidence pack item states an explicit open-source license, and the App/cloud components are explicitly described as closed. missing for 10: explicit license file/name (MIT, Apache, etc.), confirmation the full product (not just CLI) is open, and independent corroboration beyond one forum remark.

   • [github] “Codex CLI is a coding agent from OpenAI that runs locally on your computer.”
   • [community] “I wish Codex App was open source. I like it, but there are always a bunch of little paper cuts that, if you were using codex cli, you could …”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   No evidence of any open-source license or public source repository for Antigravity; it appears closed-source (VSCode fork distributed as binary download, third-party unofficial extensions noted). Nothing in the docs or community reports references source availability or a license.

   ⚑ flag

4. ai-native userSelf-host the core product

   weight 3 · round drawn
   Codex—none0/10

   Codex CLI runs locally but requires signing into a ChatGPT account or OpenAI API key, and the core inference/model and cloud environments are OpenAI-hosted only; there is no self-hosted backend option. A commenter explicitly wishes the Codex App were open source, implying it is not, which forecloses self-hosting the core product.

   • [github] “We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan.”
   • [github] “You can also use Codex with an API key, but this requires additional setup.”
   • [community] “I wish Codex App was open source. I like it, but there are always a bunch of little paper cuts that, if you were using codex cli, you could …”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   No evidence anywhere in the pack indicates Antigravity can be self-hosted; it is described only as a downloadable desktop app/IDE/CLI/SDK connecting to Google's cloud-hosted models, with account/entitlement gating and TOS restrictions mentioned in community reports, but no self-hosted server or on-prem deployment option is documented.

   • [claimed-docs] “Visit antigravity.google/download to download Google Antigravity 2.0. Select your operating system below”
   • [claimed-docs] “Antigravity 2.0 serves as your AI agents’ central command center, providing a unified platform to launch, monitor, and orchestrate their act…”
   • [community] “don't buy Google AI subscription before you confirm you have 'Antigravity entitlement'... You can have verified account, bank card added, ac…”
   • [community] “Google Antigravity TOS: 3rd party usage can get Google account suspended. My friend got a ban by using Pi agent with Antigravity. They un-ba…”

   proof ↗⚑ flag

Authentication

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

   weight 2 · round to Codex
   Codex~partialcommunity5/10

   GitHub docs confirm Codex CLI supports API key authentication as an alternative to ChatGPT account login, but note it 'requires additional setup,' and the account-login flow (Sign in with ChatGPT) is the recommended default. Missing for 10: detailed API-key setup documentation, first-party quickstart parity with account login, and independent confirmation that API-key auth is fully feature-equivalent (e.g. codex-comm-5 shows some newer models aren't even available via API yet).

   • [github] “We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan.”
   • [github] “You can also use Codex with an API key, but this requires additional setup.”
   • [community] “gpt-5.3-codex isn't available on the API yet — 'We are working to safely enable API access soon.'”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   Evidence shows Antigravity requires a Google account/login and even ties usage to 'Antigravity entitlement' on that account (comm-19), with account-level bans possible (comm-17, comm-20); no docs or CLI reference mention an API-key authentication mode as an alternative to account login.

   • [community] “Google Antigravity TOS: 3rd party usage can get Google account suspended. My friend got a ban by using Pi agent with Antigravity. They un-ba…”
   • [community] “don't buy Google AI subscription before you confirm you have 'Antigravity entitlement'... You can have verified account, bank card added, ac…”
   • [community] “Banning the entire account rather than AI access is wildly user hostile... And then you get to fight the support bots and eventually go to t…”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex~partialclaimed5/10

   Codex supports signing in with a ChatGPT Business/Enterprise/Edu account (codex-gh-3, codex-gh-7) and OpenAI's platform offers RBAC to scope access at org/project level (codex-docs-28), suggesting enterprise-grade authentication and access control exist. However, there is no explicit documentation of SSO/SAML/OIDC federation with enterprise identity providers (e.g., Okta, Azure AD) specific to Codex, nor details on how ChatGPT Enterprise auth ties into RBAC for Codex usage. Missing for 10: explicit SSO/SAML/OIDC integration docs, enterprise IdP federation details, and independent confirmation of compliance-grade auth flows for Codex specifically.

   • [github] “We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan.”
   • [github] “Run `codex` and select **Sign in with ChatGPT**. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Busi…”
   • [claimed-docs] “Role-based access control (RBAC) lets you decide who can do what across your organization and projects—both through the API and in the Dashb…”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   No evidence of SSO/SAML/OIDC, Google Workspace/Cloud IAM enterprise login, or any enterprise identity federation for Antigravity; docs mention only Google account sign-in and entitlement issues, with community reports of account suspensions rather than enterprise auth support. Missing for 10: SSO/SAML/OIDC support, Google Cloud IAM or Workspace admin console integration, enterprise provisioning/SCIM documentation.

   • [community] “don't buy Google AI subscription before you confirm you have 'Antigravity entitlement'... You can have verified account, bank card added, ac…”
   • [community] “Banning the entire account rather than AI access is wildly user hostile... And then you get to fight the support bots and eventually go to t…”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex✓fullclaimed9/10

   GitHub docs explicitly recommend signing in with ChatGPT to use Codex under existing Plus, Pro, Business, Edu, or Enterprise subscription plans, with API key as an alternative for those without such plans, directly confirming subscription-based sign-in. missing for 10: independent hands-on confirmation of the sign-in flow itself (evidence focuses on capability descriptions rather than a walkthrough).

   • [github] “We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan.”
   • [github] “Run `codex` and select **Sign in with ChatGPT**. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Busi…”
   • [github] “Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, …”
   • [github] “You can also use Codex with an API key, but this requires additional setup.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   No documentation describes signing in with an existing Google AI/Gemini subscription plan to unlock Antigravity access, and community reports directly state that users with an active AI Pro subscription still could not use even the free tier without a separate 'Antigravity entitlement.' missing for 10: any first-party docs describing subscription-based sign-in, evidence of successful subscription-linked access, and confirmation that paid Google AI plans map directly to Antigravity usage.

   • [community] “don't buy Google AI subscription before you confirm you have 'Antigravity entitlement'... You can have verified account, bank card added, ac…”
   • [community] “Google Antigravity TOS: 3rd party usage can get Google account suspended. My friend got a ban by using Pi agent with Antigravity. They un-ba…”
   • [community] “On the pricing page it says free individual plan with 'generous rate limits'. I gave it an HTML file and 2 minutes later got: 'Model quota l…”

   proof ↗⚑ flag

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

   weight 1 · round to Codex
   Codex✓fullclaimed8/10

   Codex CLI explicitly recommends signing in with a ChatGPT account (Plus/Pro/Business/Edu/Enterprise) to use Codex without an API key, with API key usage noted as an alternative requiring additional setup. This directly matches the story of personal-account sign-in without managing API keys, though the exact free-tier scope/limits aren't detailed. Missing for 10: explicit confirmation of a genuinely free tier (vs. paid ChatGPT plans) and independent corroboration of the login flow's simplicity.

   • [github] “We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan.”
   • [github] “You can also use Codex with an API key, but this requires additional setup.”
   • [github] “Run `codex` and select **Sign in with ChatGPT**. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Busi…”

   proof ↗⚑ flag

   Google Antigravity!disputedcontradicted3/10

   Vendor pages advertise a free individual plan with no mention of API key management, implying sign-in-with-personal-account access, but community hands-on reports directly contradict the free-tier promise — one user got a 'Model quota limit exceeded' error within minutes despite the 'generous rate limits' claim, and another describes being locked out of even the free tier due to an 'Antigravity entitlement' gate despite having an active subscription. missing for 10: first-party documentation explicitly describing the personal-account sign-in flow and free-tier terms, and independent confirmation that free-tier access works reliably without unexpected quota/entitlement blocks.

   • [community] “On the pricing page it says free individual plan with 'generous rate limits'. I gave it an HTML file and 2 minutes later got: 'Model quota l…”
   • [community] “don't buy Google AI subscription before you confirm you have 'Antigravity entitlement'... You can have verified account, bank card added, ac…”
   • [claimed-docs] “Visit antigravity.google/download to download Google Antigravity 2.0. Select your operating system below”

   proof ↗⚑ flag

Model choice

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

   weight 1 · round drawn
   Codex—none0/10

   Evidence shows Codex lets users manually choose the model and reasoning effort ('Stay in control: Choose the model, reasoning effort, permissions...') rather than any automatic best-model-per-task selection; no docs or community evidence describe an automatic model-routing/selection feature tied to cost or task type.

   • [claimed-docs] “Stay in control: Choose the model, reasoning effort, permissions, and commands that fit the task.”
   • [community] “The main issue I have with Codex is that the best model is insanely slow, except at nights and weekends when Silicon Valley goes to bed... I…”
   • [community] “First thoughts using gpt-5.3-codex-spark in Codex CLI: Blazing fast but it definitely has a small model feel... It has to be prompted to do …”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   Docs describe a manual model selector dropdown where users choose the reasoning model themselves (antigravity-docs-16), not an automatic 'best model per task' selection mechanism; no evidence anywhere of automatic model routing or task-based model optimization.

   • [claimed-docs] “Users can select which reasoning model they want to use within the model selector drop-down under the conversation prompt box”

   proof ↗⚑ flag

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

   weight 2 · round to Google Antigravity
   Codex—none0/10

   Docs confirm Codex lets users 'Choose the model, reasoning effort, permissions' (codex-docs-31), but this refers to selecting among OpenAI's own Codex/GPT models, not switching between different AI providers (e.g., Anthropic, Google). No evidence shows Codex supports plugging in or selecting non-OpenAI models/providers within a session.

   • [claimed-docs] “Stay in control: Choose the model, reasoning effort, permissions, and commands that fit the task.”
   • [github] “We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan.”
   • [github] “You can also use Codex with an API key, but this requires additional setup.”

   proof ↗⚑ flag

   Google Antigravity✓fullcommunity8/10

   Docs explicitly describe a model selector dropdown for choosing reasoning models, and community hands-on evidence confirms multiple providers (Gemini 3 Pro, Claude Sonnet 4.5, GPT-OSS 120B) are selectable, not locked to Gemini only. Missing for 10: pricing/tier restrictions per model and independent benchmarking of model-switching quality across providers.

   • [claimed-docs] “Users can select which reasoning model they want to use within the model selector drop-down under the conversation prompt box”
   • [community] “I went ahead and downloaded it, it looks to be a VSCode fork very similar to Cursor, with support for Gemini 3 Pro, Claude Sonnet 4.5, and G…”
   • [community] “Nice to see that it's not locked to just Gemini models.”

   proof ↗⚑ flag

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

   weight 2 · round drawn
   Codex—none0/10

   No evidence in the pack mentions data residency, regional storage options, or geographic controls for where Codex data is stored; the pack covers RBAC, MCP, CLI features, and cloud task execution but nothing about choosing a storage region.

   ⚑ flag

   Google Antigravity—none0/10

   No evidence pack item mentions data residency, region selection, or storage location controls; only a telemetry on/off toggle is documented, which does not address data residency. Missing for 10: any documentation of regional data storage options, residency guarantees, or enterprise data-location controls.

   ⚑ flag

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

   weight 3 · round to Google Antigravity
   Codex—none0/10

   The evidence pack contains no mention of data-training opt-out controls, enterprise data usage policies, or privacy settings for excluding user data from model training; it covers CLI features, MCP, RBAC, and community sentiment but nothing about training-data exclusion.

   ⚑ flag

   Google Antigravity~partialclaimed5/10

   Antigravity's settings docs mention a Telemetry toggle to enable/disable sharing interaction logs 'to improve models,' which is the only evidence addressing training-data opt-out; there's no further detail on scope, default state, or enterprise data-processing guarantees. Missing for 10: independent verification the toggle actually excludes data from training, clarity on default setting, and any enterprise/DPA-level documentation of data usage.

   • [claimed-docs] “toggle Telemetry (enable/disable sharing interaction logs to improve models)”

   proof ↗⚑ flag

3. ai-native userControl data retention and deletion

   weight 2 · round to Google Antigravity
   Codex—none0/10

   No evidence pack items address data retention controls, deletion policies, or configurable retention windows for Codex; RBAC docs address access control, not retention/deletion. Missing for 10: any documentation of data retention settings, deletion APIs/workflows, or retention policy configuration.

   ⚑ flag

   Google Antigravity~partialclaimed3/10

   Docs mention a Telemetry toggle to enable/disable sharing interaction logs, which is a privacy-related control, but there is no documented mechanism for viewing, exporting, or deleting stored data/history, nor any stated retention policy. Missing for 10: explicit data deletion controls, data export/retention policy documentation, and independent confirmation these settings work as described.

   • [claimed-docs] “toggle Telemetry (enable/disable sharing interaction logs to improve models)”

   proof ↗⚑ flag

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

   weight 2 · round to Google Antigravity
   Codex—none0/10

   No evidence in the pack mentions telemetry, usage tracking, data collection settings, or an opt-out mechanism for Codex; the docs and community threads cover features like MCP, CLI usage, and performance but never privacy/telemetry controls.

   ⚑ flag

   Google Antigravity✓fullclaimed7/10

   Docs confirm a settings toggle to enable/disable telemetry ('sharing interaction logs to improve models'), giving users a direct opt-out. Missing for 10: independent/hands-on confirmation that the toggle fully stops all data collection, and no detail on what telemetry remains even when disabled.

   • [claimed-docs] “toggle Telemetry (enable/disable sharing interaction logs to improve models)”

   proof ↗⚑ flag

Data governance

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

   weight 1 · round to Google Antigravity
   Codex—none0/10

   No evidence in the pack addresses data usage or training opt-out policies for code/prompts; RBAC and MCP docs are unrelated to this axis. Missing for 10: any enterprise data-usage/training opt-out policy documentation, admin controls for opting out, or third-party confirmation of such a policy.

   ⚑ flag

   Google Antigravity~partialclaimed5/10

   Docs mention a Telemetry toggle to 'enable/disable sharing interaction logs to improve models,' which functions as an opt-out from data being used for model improvement, but there is no explicit documentation framing this as a training opt-out for enterprise/engineering-lead governance needs (e.g., no data-processing agreement, no distinction between prompts/code vs telemetry, no enterprise admin-level control). Missing for 10: explicit statement that code/prompts are excluded from training, org-wide/admin-level enforcement of the opt-out, and independent confirmation the toggle actually stops training use.

   • [claimed-docs] “toggle Telemetry (enable/disable sharing interaction logs to improve models)”

   proof ↗⚑ flag

Pr review

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

   weight 3 · round to Codex
   Codex~partialclaimed6/10

   Codex docs explicitly describe inspecting diffs and opening a pull request when cloud work is ready (codex-docs-5), and CLI docs note reviewing changes 'before you commit or open a pull request' (codex-docs-45), implying git workflow integration. However, staging changes, writing commit messages, and creating branches are not explicitly documented as first-class agent actions — they are only implied via general local repo access and command execution (codex-docs-9, codex-docs-30, codex-docs-17). Missing for 10: explicit documentation of commit-message generation, branch creation, and staging as named agent capabilities, plus independent hands-on confirmation of full PR workflow automation.

   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Start Codex in a repository to explore unfamiliar code, plan a change, edit files, and run your local development tools.”
   • [claimed-docs] “Work against your local repository: Let Codex inspect files, make edits, and run the tools already installed on your machine.”

   proof ↗⚑ flag

   Google Antigravity~partialclaimed3/10

   Antigravity's agents can operate the terminal and natively support Git worktrees, which implies they could run git commands like staging, committing, and branching, but no documentation explicitly describes agent-driven commit message generation, branch creation, or PR opening (e.g., GitHub integration). Missing for 10: explicit docs on commit-message authoring, branch creation workflow, and pull-request creation/integration with GitHub/GitLab.

   • [claimed-docs] “Worktree support: Projects natively support Git worktrees, allowing agents to operate in isolated background folders.”
   • [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
   • [claimed-docs] “Build AI agents that autonomously read files, run commands, edit code, and more.”

   proof ↗⚑ flag

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

   weight 3 · round to Codex
   Codex~partialclaimed5/10

   Codex CLI/cloud ships a dedicated 'review' capability that inspects uncommitted changes, a commit, or a base branch and reports prioritized findings without touching the working tree, and cloud tasks can be kicked off from GitHub PRs and later opened as PRs. However, there is no evidence of an automatic, PR-triggered review bot that comments on every pull request without manual invocation. missing for 10: evidence of automatic triggering on every PR (e.g., GitHub App/webhook auto-review), evidence of inline PR comments, independent confirmation of review quality on real PRs.

   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Start work in Codex cloud from GitHub pull requests, GitLab merge requests and issues, Linear issues, or Slack channels and threads.”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   Antigravity offers in-editor 'Review Changes' diff viewing and Artifact-based plan review, but there is no evidence of a GitHub/GitLab pull-request bot or CI-integrated review that automatically posts contextual feedback on every PR. The CLI headless mode allows scripting into CI, but no docs describe an automated PR-review workflow.

   • [claimed-docs] “Planning Mode: The agent plans thoroughly before executing tasks... produces structured implementation plans called Artifacts”
   • [claimed-docs] “The agent always halts and requests your explicit approval before proceeding with proposed changes.”
   • [claimed-docs] “Added a "Hide Whitespace Changes" option to the Review Changes overflow menu and file diff viewers to filter out whitespace-only edits.”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”

   proof ↗⚑ flag

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

   weight 3 · round to Codex
   Codex✓fullclaimed8/10

   Codex CLI has a dedicated review command that inspects diffs against uncommitted changes, a commit, or a base branch, reporting prioritized findings without modifying the working tree, plus cloud/web flows to inspect summaries and diffs before opening a PR. Missing for 10: independent/hands-on corroboration of the review command's accuracy and any CI-integrated check-running beyond exec/scripts.

   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Inspect the summary and diff, request a follow-up, or open a pull request when the result is ready.”
   • [claimed-docs] “Compose with scripts and CI: Use Codex interactively or call codex exec from repeatable workflows and pipelines.”

   proof ↗⚑ flag

   Google Antigravity~partialcommunity6/10

   Docs describe a Review Changes/diff viewer (with whitespace filtering, syntax highlighting) and Artifacts containing code diffs, plus mandatory human approval before changes are applied, and subagents/CI headless mode that can run tests. This covers diff inspection and pre-merge gating, but there's no dedicated 'run checks' feature (e.g., integrated linting/test-run summary) beyond subagent test delegation, and no independent hands-on confirmation that this workflow reliably catches problems — community reports instead highlight safety failures (accidental deletion, data exfiltration) that occurred despite review/approval mechanisms. Missing for 10: independent verification that diff review + checks actually catch bugs pre-merge, and a dedicated automated check/test-report feature beyond ad-hoc subagent delegation.

   • [claimed-docs] “Planning Mode: The agent plans thoroughly before executing tasks... produces structured implementation plans called Artifacts”
   • [claimed-docs] “The agent always halts and requests your explicit approval before proceeding with proposed changes.”
   • [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
   • [claimed-docs] “Added a "Hide Whitespace Changes" option to the Review Changes overflow menu and file diff viewers to filter out whitespace-only edits.”
   • [claimed-docs] “Code and data artifacts like SQL and JSONL files now open in a virtualized viewer with syntax highlighting and line numbers”
   • [claimed-docs] “an agent can delegate tasks—such as running tests or performing extensive codebase searches—to dedicated subagents.”
   • [claimed-docs] “Run Antigravity CLI non-interactively to script agent tasks, integrate with CI pipelines, and capture machine-readable output.”
   • [community] “Google Antigravity just deleted the contents of whole drive - came down to commanding a deletion of a 'directory with space in the name' wit…”
   • [community] “absolutely no sympathy for someone running Antigravity in Turbo mode (this is not the default and it clearly states that Antigravity auto-ex…”

   proof ↗⚑ flag

Safe execution

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

   weight 2 · round to Codex
   Codex~partialclaimed6/10

   Codex documents fine-grained control over external tool access at the session/repo level: engineers can add/remove local or remote MCP servers, inspect available tools before they're used, and set permission boundaries for edits/commands via /permissions (codex-docs-16, codex-docs-38, codex-docs-39, codex-docs-46). This gives an engineer meaningful control over which integrations the agent can reach, and RBAC exists for org/project-level API access (codex-docs-28), but that RBAC is about API/dashboard permissions, not specifically about restricting agent tool/integration access org-wide for a lead managing a team's Codex usage. Missing for 10: evidence of centralized, lead-enforced policy that restricts which MCP servers/tools individual developers can enable (vs. per-session self-configuration), and independent confirmation this control actually prevents unauthorized tool access in practice.

   • [claimed-docs] “Add local or remote MCP servers, authenticate when needed, and inspect the tools available to the current session before Codex uses them.”
   • [claimed-docs] “Connect external tools with MCP — codex mcp: Add local or remote MCP servers, authenticate when needed, and inspect the tools available to t…”
   • [claimed-docs] “Set the boundaries for each run — /permissions: Choose when Codex can edit files or run commands without asking, and inspect the active sand…”
   • [claimed-docs] “In the `codex` TUI, use `/mcp` to see your active MCP servers.”
   • [claimed-docs] “Role-based access control (RBAC) lets you decide who can do what across your organization and projects—both through the API and in the Dashb…”

   proof ↗⚑ flag

   Google Antigravity!disputedcontradicted5/10

   Antigravity docs describe granular controls—Deny/Ask/Allow permission lists, MCP server configuration, plugins bundling MCP servers, and sandboxing that blocks sensitive files—giving engineering leads levers to restrict tool/integration access (antigravity-docs-23, antigravity-docs-42, antigravity-docs-12, antigravity-docs-28, antigravity-docs-48). However, independent security reports document that these controls were bypassed in practice: Gemini accessed .env files despite being configured not to, and the default Allowlist shipped with webhook.site, which was used as a live exfiltration vector—directly contradicting the claim that admins can reliably restrict external access (antigravity-comm-11, antigravity-comm-12, antigravity-comm-13). Missing for 10: evidence of a fix/patch to these bypasses, and no first-party acknowledgment/remediation documentation confirming the control now holds as designed.

   • [claimed-docs] “Permissions are evaluated across three distinct access lists: Deny... Ask... Allow”
   • [claimed-docs] “Permissions are evaluated across three distinct access lists: Deny...Ask...Allow”
   • [claimed-docs] “Access plugins, MCP, skills, and hooks configurations instantly via slash commands, quickly enhancing your workflow.”
   • [claimed-docs] “Plugins are namespaced bundles that allow you to extend Antigravity’s capabilities by grouping skills, rules, MCP servers, and hooks into a …”
   • [claimed-docs] “Sensitive files like ~/.ssh and .env are blocked, anything not explicitly mounted is invisible inside the sandbox”
   • [community] “Google Antigravity exfiltrates data via indirect prompt injection attack: Gemini is not supposed to have access to .env files with default s…”
   • [community] “The default Allowlist provided with Antigravity includes 'webhook.site', which was used as an exfiltration vector for secrets.”
   • [community] “Antigravity was also vulnerable to the classic Markdown image exfiltration bug, reported a few days prior and flagged as 'intended behavior'…”

   proof ↗⚑ flag

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

   weight 2 · round to Codex
   Codex✓fullcommunity7/10

   First-party docs explicitly describe sandboxed execution: Codex lets you 'choose when Codex can edit files or run commands without asking, and inspect the active sandbox and writable roots' (codex-docs-17), and cloud tasks run in 'isolated cloud environments' with configurable dependencies/tools (codex-docs-1, codex-docs-4). This directly matches the engineering-lead's need for sandboxed code/tool interaction, though network-resource sandboxing specifics are not spelled out and there's no independent hands-on verification of sandbox robustness (a community comment raises but does not concretely confirm a sandbox-bypass issue). Missing for 10: explicit documentation of network-level sandbox controls, and independent/hands-on confirmation that the sandbox reliably contains tool/network access.

   • [claimed-docs] “Choose when Codex can edit files or run commands without asking, and inspect the active sandbox and writable roots before you continue.”
   • [claimed-docs] “Run tasks in isolated cloud environments, work in parallel, and start work from the web, GitHub, GitLab, Linear, or Slack.”
   • [claimed-docs] “Configure the dependencies, tools, variables, and setup steps each repository needs.”
   • [community] “Do people really want codex to have control over their computer and apps? I'm still paranoid about keeping things securely sandboxed.”

   proof ↗⚑ flag

   Google Antigravity!disputedcontradicted4/10

   Antigravity CLI docs describe a real sandbox mechanism (sensitive files like ~/.ssh and .env blocked, unmounted paths invisible) plus a permission allow/ask/deny system, suggesting sandboxed tool/network access is a documented feature. However, independent reports concretely contradict this: Gemini bypassed its own .env protection to exfiltrate secrets via indirect prompt injection using an allow-listed exfiltration endpoint, a known markdown-image exfiltration bug was dismissed as 'intended behavior,' and unrestrained terminal auto-execution led to a user's entire drive being deleted — showing the sandbox/permission boundary is not reliably enforced in practice. Missing for 10: consistent enforcement of sandbox boundaries against prompt-injection/exfiltration, first-party acknowledgment/fix of these incidents, and independent verification that the CLI's stated sandbox extends to the IDE agent's file/network access.

   • [claimed-docs] “Sensitive files like ~/.ssh and .env are blocked, anything not explicitly mounted is invisible inside the sandbox”
   • [claimed-docs] “Permissions are evaluated across three distinct access lists: Deny... Ask... Allow”
   • [claimed-docs] “MCP lets Antigravity fetch structured context directly or execute safe actions on your behalf when needed.”
   • [community] “Google Antigravity exfiltrates data via indirect prompt injection attack: Gemini is not supposed to have access to .env files with default s…”
   • [community] “The default Allowlist provided with Antigravity includes 'webhook.site', which was used as an exfiltration vector for secrets.”
   • [community] “Antigravity was also vulnerable to the classic Markdown image exfiltration bug, reported a few days prior and flagged as 'intended behavior'…”
   • [community] “Google Antigravity just deleted the contents of whole drive - came down to commanding a deletion of a 'directory with space in the name' wit…”
   • [community] “The most useful suggestion from the Reddit thread: turn off 'Terminal Command Auto Execution' via File > Preferences > Antigravity Settings …”
   • [community] “absolutely no sympathy for someone running Antigravity in Turbo mode (this is not the default and it clearly states that Antigravity auto-ex…”

   proof ↗⚑ flag

Security checks

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

   weight 1 · round drawn
   Codex—none0/10

   No evidence anywhere in the pack mentions license detection, public-code matching, or provenance references for AI-suggested code; Codex's review features (codex-docs-10, -41, -45) only cover code quality/prioritized findings, not license/public-code attribution.

   ⚑ flag

   Google Antigravity—none0/10

   No evidence in the pack mentions license compliance checks, public-code/OSS matching, provenance detection, or any similar review-safety feature for AI-suggested code; the docs focus on agents, artifacts, permissions, and workflow tooling with no mention of license scanning.

   ⚑ flag

2. developerGet contextual explanations and automatic fixes for security vulnerabilities

   weight 2 · round to Codex
   Codex~partialclaimed3/10

   Codex CLI has a dedicated review command that inspects uncommitted changes, commits, or branches and reports 'prioritized findings' (codex-docs-10, codex-docs-41, codex-docs-45), which could surface security issues, and as a general coding agent it can edit files/run commands. However, the review feature explicitly reports findings 'without modifying your working tree,' meaning it does not auto-fix, and no evidence specifically frames this as security-vulnerability detection/explanation with automatic remediation. missing for 10: explicit security-vulnerability scanning/explanation feature, evidence of automatic fix application (vs. just flagging), and any independent confirmation that Codex reliably identifies/fixes security issues.

   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Review changes before they ship: Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized f…”
   • [claimed-docs] “Run a dedicated review against uncommitted changes, a commit, or a base branch. Codex reports prioritized findings without modifying your wo…”
   • [claimed-docs] “Work against your local repository: Let Codex inspect files, make edits, and run the tools already installed on your machine.”

   proof ↗⚑ flag

   Google Antigravity—none0/10

   No evidence that Antigravity provides security-vulnerability-specific explanations or automatic fixes; the docs describe general agentic coding, planning, and review features but never mention vulnerability scanning or security remediation. Community evidence instead highlights security *problems* in Antigravity itself (prompt injection exfiltration), not a vulnerability-fixing capability for users' code.

   ⚑ flag