Cursor vs Google Antigravity
Google Antigravity wins · 15–28 (26 drawn)
Agenticness — how well agents can access and operate the productAgenticness
How well agents can access and operate the product
Agent access
ai-native userPoint an agent at llms.txt or agent-oriented docs
weight 2 · round to Google AntigravityCursornone0/10No evidence pack item mentions llms.txt, agent-oriented documentation ingestion, or a mechanism to point Cursor's agent at such files; only generic doc/MCP/tooling references are present. missing for 10: any mention of llms.txt support, crawling agent-oriented doc formats, or a documented feature for feeding external agent docs to Cursor's agent.
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”
ai-native userRun the product headlessly / in CI for automation
weight 2 · round to Google AntigravityCursor ships an official CLI (cursor.com/cli, curl installer) and background/cloud agents that run 'on schedules or triggers' to build and fix software autonomously, which implies non-interactive/headless automation. However, there is no explicit documentation of CI pipeline integration, exit codes, or scripting examples for pipelines. Missing for 10: explicit CI/CD integration docs (e.g., GitHub Actions example), documented headless flags/exit-code behavior, and independent confirmation of CLI use in automated pipelines.
- [probe] “official CLI documented at https://cursor.com/cli”
- [claimed-docs] “curl https://cursor.com/install -fsS | bash”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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.”
ai-native userPlug MCP servers into this product so it can use their tools
weight 3 · round drawnCursor's docs explicitly describe MCP support: connecting to external tools/data sources, marketplace one-click install with OAuth, custom JSON server configuration, toggling servers, and enterprise admin controls over allowed servers. This directly matches the story of plugging in MCP servers so the agent can use their tools. Missing for 10: independent hands-on verification of MCP tool usage in practice and no community corroboration of the feature's reliability.
- [claimed-docs] “Model Context Protocol (MCP) enables Cursor to connect to external tools and data sources.”
- [claimed-docs] “Click "Add to Cursor" on a marketplace entry to install it and authenticate with OAuth.”
- [claimed-docs] “Configure custom MCP servers with a JSON file”
- [claimed-docs] “Enterprise admins can control which MCP servers users may run from the Cursor dashboard.”
- [claimed-docs] “Toggle servers on/off without removing them”
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 …”
ai-native userUse an official CLI
weight 2 · round drawnCursor documents an official CLI with an install command (curl https://cursor.com/install) and a dedicated CLI docs page (cursor.com/cli), confirming a first-party terminal tool for AI-native workflows. Missing for 10: independent/hands-on corroboration of CLI capabilities and depth of documentation beyond install instructions.
- [claimed-docs] “curl https://cursor.com/install -fsS | bash”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [probe] “official CLI documented at https://cursor.com/cli”
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”
ai-native userDrive the product through a documented public API
weight 3 · round to Google AntigravityEvidence shows an official CLI (cursor.com/cli) that lets users invoke Cursor from scripts, which partially satisfies 'driving the product programmatically,' but there is no documented public REST/SDK API, authentication scheme, or endpoint reference — MCP docs describe Cursor consuming external tools, not exposing itself as an API. Missing for 10: documented REST/GraphQL API, SDK/client libraries, API authentication and rate-limit docs, independent corroboration of programmatic usage.
- [probe] “official CLI documented at https://cursor.com/cli”
- [claimed-docs] “curl https://cursor.com/install -fsS | bash”
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…”
ai-native userIssue scoped/least-privilege API credentials for an agent
weight 2 · round to Google AntigravityCursornone0/10No evidence Cursor lets users mint scoped or least-privilege API credentials for agents; docs cover MCP server toggling and enterprise admin control of which servers can run, but nothing about issuing scoped/limited API keys or credentials specifically for agent use.
Google Antigravitydisputedcontradicted4/10Antigravity 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.”
ai-native userBuild against official SDKs
weight 2 · round to Google AntigravityCursornone0/10Evidence shows Cursor offers a CLI, MCP integration, and marketplace extensions, but there is no mention of any official SDK (e.g., a documented library/API package) for developers to build against Cursor itself.
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…”
ai-native userSubscribe to events via webhooks
weight 2 · round drawnCursornone0/10Evidence covers MCP integration, background agents, and IDE integrations, but there is no mention of a webhook subscription mechanism for external event notifications.
Google Antigravitynone0/10No 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…”
Agentic features
ai-native userGet AI-generated insights and suggestions from my data inside the product
weight 2 · round to CursorCursor's core value proposition is analyzing the user's codebase to surface AI-generated insights (tracing repo structure, finding root causes, reviewing diffs) and suggestions for next actions, as documented across multiple first-party docs. Missing for 10: independent/hands-on evidence validating the accuracy or depth of these insights, and no detail on insight types beyond code-centric suggestions (e.g., data analytics or business data outside code).
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
- [claimed-docs] “Scope changes, use Plan Mode, and ship bigger work with confidence”
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
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…”
ai-native userSet up automations that run autonomously in the background
weight 2 · round drawnCursor explicitly documents 'always-on agents that run on schedules or triggers to build, maintain, and fix your software' and 'fleets of agents that work in parallel for hours or days,' directly matching autonomous background automation. This is first-party vendor documentation without independent hands-on corroboration of scheduling/triggers working reliably. Missing for 10: independent/community verification that scheduled/triggered background agents work reliably in practice, and more detail on trigger configuration options.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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.”
ai-native userDelegate tasks to a built-in AI assistant inside the product
weight 3 · round to CursorCursor's docs clearly describe delegating tasks to built-in agents that plan, code, test, and demo work end-to-end while the user focuses on review/decisions, including background/parallel agents and always-on scheduled agents. This is a core, heavily documented capability of the product, though independent hands-on validation of agent task quality is thin (only general community commentary, some critical, exists). Missing for 10: deeper independent verification of agent task success rates beyond vendor docs.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
- [claimed-docs] “Scope changes, use Plan Mode, and ship bigger work with confidence”
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 …”
ai-native userOperate the product with natural-language commands
weight 2 · round drawnCursor's core interaction model is natural-language driven agents that plan, code, test, and operate across terminal/Slack/GitHub (cursor-docs-2, cursor-docs-8, cursor-docs-9, cursor-docs-10, cursor-docs-11), consistent with an AI-native product. Missing for 10: independent hands-on evidence specifically validating natural-language command reliability/accuracy (community evidence focuses on bugginess/pricing complaints unrelated to NL command capability itself).
- [claimed-docs] “Scope changes, use Plan Mode, and ship bigger work with confidence”
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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 …”
Api quality
ai-native userDownload a machine-readable API spec (OpenAPI or equivalent)
weight 2 · round drawnCursornone0/10No evidence of Cursor publishing a downloadable OpenAPI or equivalent machine-readable API spec; docs reference MCP config and CLI but not an API spec.
Google Antigravitynone0/10A 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…”
ai-native userRely on versioned APIs with a documented deprecation policy
weight 2 · round drawnCursornone0/10No evidence in the pack mentions API versioning or a deprecation policy for Cursor's APIs (CLI, extensions, or MCP config); docs cover features like MCP setup, agents, and integrations but nothing about version stability guarantees or deprecation timelines.
Google Antigravitynone0/10No 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…”
Automation depth — how much of the product can run unattendedAutomation depth
How much of the product can run unattended
ai-native userPerform bulk operations across many items at once
weight 2 · round to Google AntigravityCursor supports launching 'fleets of agents' in parallel and always-on scheduled/triggered agents, which enables some multi-item automation, but there's no direct evidence of bulk operations across many discrete items (e.g., bulk file edits, batch refactors, or multi-repo operations) as a first-class feature. missing for 10: explicit documentation or hands-on evidence of bulk/batch operations across many items (files, tickets, repos), user-facing UI for selecting many items at once, and independent corroboration of this working in practice.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
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.”
ai-native userDefine rules that trigger actions automatically on events
weight 3 · round to Google AntigravityCursor docs describe 'always-on agents that run on schedules or triggers' and a way to 'add rules' from one place, matching the idea of rule-based automation triggered by events. However the evidence pack doesn't detail how rules are authored/scoped to specific events beyond the marketing blurb, and there's no independent/hands-on confirmation of this automation working as described. Missing for 10: concrete rule-definition syntax/examples, independent verification that scheduled/triggered agents reliably fire on events, and detail on event types supported.
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Add plugins, skills, MCPs, and rules from one place”
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.”
ai-native userSchedule recurring jobs or workflows
weight 2 · round to Google AntigravityCursor documents 'always-on agents that run on schedules or triggers to build, maintain, and fix your software,' directly matching recurring scheduled workflow automation, alongside parallel agent fleets for ambitious tasks. Missing for 10: independent hands-on verification of scheduling reliability, details on trigger configuration options, and any community corroboration of this specific feature working in practice.
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
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”
ai-native userVersion, review, and roll back my automations
weight 1 · round drawnCursornone0/10Evidence shows Cursor can inspect diffs and review changes before merge, but there is no documented capability to version, review, or roll back the automations themselves (e.g., scheduled/always-on agents, rules, MCP configs) as distinct artifacts with history/rollback support.
Google Antigravitynone0/10Evidence 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.
Autonomy agents — stories about autonomy agents in this arenaAutonomy agents
Stories about autonomy agents in this arena
Background execution
ai-native userHave a cloud agent build, test, and demo a feature end-to-end for my review
weight 2 · round to CursorCursor's docs explicitly describe cloud/background agents that 'use their own computers to build, test, and demo features end to end for you to review,' plus the ability to launch fleets of agents working in parallel for hours/days, and always-on scheduled agents — directly matching the story. Corroboration is entirely first-party marketing/docs rather than independent hands-on verification of an actual demo workflow. Missing for 10: independent/hands-on evidence confirming the build-test-demo loop works reliably end-to-end, and detail on what 'demo' concretely produces (e.g., preview links, recordings).
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
developerDelegate longer-running coding tasks to run in the background in an isolated cloud environment
weight 3 · round to CursorCursor documents cloud/background agents ('Agents use their own computers to build, test, and demo features end to end', 'Launch fleets of agents that work in parallel on ambitious tasks for hours or days', and hand-off delegation while the developer focuses elsewhere), matching the isolated cloud-background-task story. Missing for 10: independent hands-on verification of the background agent's isolation/reliability and details on session duration limits or failure modes.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
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.”
Parallel agents
ai-native userLaunch fleets of autonomous agents that work in parallel on different tasks for hours or days
weight 2 · round to CursorFirst-party marketing/docs explicitly state the exact capability: "Launch fleets of agents that work in parallel on ambitious tasks for hours or days," plus supporting evidence of background/always-on agents and agents using their own compute to build/test/demo. No independent hands-on verification of multi-day parallel fleet execution is present, and no community corroboration confirms this specific feature works at scale. Missing for 10: independent/hands-on validation of parallel agent fleets running for hours/days, details on concurrency limits or reliability over long runs.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
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.”
developerRun several task attempts in parallel and compare results before choosing one
weight 1 · round to CursorCursor's docs describe launching 'fleets of agents that work in parallel on ambitious tasks for hours or days,' directly supporting parallel task execution, and agents run in isolated environments for review before merging changes. However, there is no explicit documentation of a UI/workflow for comparing multiple parallel attempts side-by-side before choosing one, and no independent/hands-on evidence corroborating this specific comparison workflow. Missing for 10: dedicated compare/diff-across-attempts feature documentation, independent verification of parallel-agent comparison in practice.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
Scheduled automation
ai-native userSet up always-on agents that run on schedules or triggers to maintain and fix my software autonomously
weight 2 · round to CursorCursor's own site directly states the capability: "Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software," plus related background-agent features (parallel fleets, agents running on their own machines) that support this workflow. Missing for 10: independent/hands-on confirmation of scheduled/triggered agents actually running reliably in practice, and more detail on trigger types/configuration.
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
Code generation — quality of generated code — correctness, style, fit to the codebaseCode generation
Quality of generated code — correctness, style, fit to the codebase
Code completion
developerReceive inline code completions and next-edit suggestions as I type
weight 3 · round to Google AntigravityCursornone0/10The evidence pack contains no first-party documentation or hands-on account describing Cursor's own inline code completion or next-edit suggestion feature; only tangential community references compare competitors' tab-completion tools (e.g., Continue, SuperMaven) without confirming or detailing Cursor's implementation. Missing for 10: any first-party doc on Cursor's Tab/inline completion feature, hands-on confirmation it works as typed, and mention of 'next-edit' suggestion behavior.
Docs mention the Editor view offers 'tab autocompletion' and 'natural language code commands' alongside the agent, which covers basic inline completion, but there is no detail on next-edit suggestions (predictive multi-line edits) or independent/hands-on confirmation of completion quality or latency. missing for 10: explicit next-edit-suggestion feature description, independent hands-on validation of autocomplete quality/reliability.
- [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”
Debugging
developerDebug a live running web application directly from my coding assistant
weight 1 · round to Google AntigravityCursornone0/10No evidence pack item describes attaching a debugger, inspecting runtime state, or interacting with a live running web app from Cursor; docs mention reproducing issues and root-causing bugs conceptually, but not live-app debugging integration (e.g., breakpoints, browser dev tools, runtime inspection). missing for 10: evidence of live debugger attach/breakpoints, browser/runtime inspection tooling, or integration with running app state.
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
Antigravity's agent can 'autonomously operate across your editor, terminal, and browser' and produces 'browser recordings' as artifacts, implying some browser-based interaction/testing, but there is no explicit documentation of live debugging features (console inspection, breakpoints, network tab, DOM inspection) for a running web app. missing for 10: explicit live-debugging tooling (breakpoints, console/network inspection), documented workflow for attaching to a running app, independent hands-on confirmation of debugging use.
- [claimed-docs] “Able to autonomously operate across your editor, terminal, and browser.”
- [claimed-docs] “Artifacts include rich markdown plans (Implementation Plans), code diffs, architecture diagrams, images, and browser recordings.”
developerDebug issues and troubleshoot using natural-language queries
weight 2 · round drawncursor-docs-3 directly claims support for reproducing issues, narrowing root cause, and verifying fixes via natural-language-driven agent workflows, and docs-1 supports tracing how a repo fits together to find bug locations. However, there's no independent/hands-on evidence corroborating debugging quality, and community evidence highlights buginess and unreliability concerns (cursor-comm-2, cursor-comm-8) that add caveats without directly contradicting the specific debugging workflow claim. Missing for 10: independent verification of debugging accuracy, concrete examples of NL-driven troubleshooting sessions, and resolution of buggy-product complaints.
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [community] “"Cursor is weird. They have a basically unused GitHub with a thousand unanswered Issues. It's so buggy in ways that VSCode isn't. I hate it.…”
- [community] “"That's a lot of money for a buggy product that is at best slightly better than its competitors."”
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”
Feature implementation
developerTurn a tracked issue into a complete pull request end-to-end
weight 3 · round to CursorCursor's docs describe agents that trace repos, plan changes, reproduce issues, inspect diffs/run checks, and integrate with issue trackers (GitHub, Linear) and PR review, which together support a full issue-to-PR workflow (cursor-docs-1 through cursor-docs-4, cursor-docs-6, cursor-docs-8–cursor-docs-12). However, there's no explicit first-party or independent case study showing a single tracked issue being turned into a merged PR end-to-end without manual intervention, and community evidence focuses on unrelated bugs/pricing complaints rather than this workflow. Missing for 10: a concrete end-to-end example/case study of issue→PR automation and independent verification that the full pipeline works reliably.
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
- [claimed-docs] “Scope changes, use Plan Mode, and ship bigger work with confidence”
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
- [claimed-docs] “Work with GitHub, GitLab, Azure DevOps, Bitbucket, JetBrains, Slack, Linear, and more”
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
Google Antigravitynone0/10Antigravity'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.”
developerDescribe a feature or bug in plain language and have the agent implement or fix it across multiple files
weight 3 · round to CursorCursor's docs describe an agent that traces repo structure, plans and scopes multi-file changes, implements features/fixes end-to-end, runs checks, and produces diffs for review — directly matching plain-language feature/bug requests across multiple files. Community evidence corroborates the product is used daily for this purpose (albeit with complaints about bugginess), without disputing the core multi-file agentic editing capability. Missing for 10: independent hands-on benchmarks showing successful multi-file fixes, and no first-party demo/case study detailing a concrete before/after example.
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
- [claimed-docs] “Scope changes, use Plan Mode, and ship bigger work with confidence”
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
- [community] “"Cursor is weird. They have a basically unused GitHub with a thousand unanswered Issues. It's so buggy in ways that VSCode isn't. I hate it.…”
- [community] “"That's a lot of money for a buggy product that is at best slightly better than its competitors."”
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…”
Maintenance automation
developerHave the agent write tests, fix lint errors, resolve merge conflicts, and update dependencies for me
weight 3 · round drawnCursor's docs describe agents that write code, run tests/checks, and 'build, maintain, and fix' software autonomously (cursor-docs-3, cursor-docs-4, cursor-docs-9, cursor-docs-12), which implies test-writing and general maintenance tasks, but there is no explicit documentation of lint-error fixing, merge-conflict resolution, or dependency-update workflows specifically. missing for 10: explicit lint-fixing examples, explicit merge-conflict-resolution examples, explicit dependency-update examples, independent hands-on verification of these specific tasks.
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
Multimodal generation
ai-native userGenerate a working app from a sketch, image, or PDF design
weight 2 · round to Google AntigravityCursornone0/10No evidence in the pack describes image/sketch/PDF-to-app generation, multimodal design input, or any UI-from-design workflow; the docs snippets cover repo navigation, plan mode, agents, MCP, and integrations but nothing about visual design inputs.
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…”
Codebase understanding — how deeply the tool maps your repo — cross-file context, architecture awareness, historyCodebase understanding
How deeply the tool maps your repo — cross-file context, architecture awareness, history
Codebase mapping
developerUnderstand how a codebase fits together to find where to start making changes
weight 3 · round drawnCursor's docs explicitly claim the ability to 'trace how a repo fits together and find the right places to start,' directly matching the story, but this is a single marketing-style doc line with no detailed walkthrough, feature docs (e.g., codebase indexing/@codebase chat), or independent corroboration of how it actually surfaces architecture understanding. Missing for 10: detailed documentation of the codebase-mapping/indexing feature itself, concrete examples of it locating relevant code, and independent/hands-on validation of accuracy.
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
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…”
developerHave the agent map and explain an entire unfamiliar codebase without manually selecting context files
weight 3 · round to Google AntigravityFirst-party docs claim Cursor can 'trace how a repo fits together and find the right places to start' (cursor-docs-1), implying automatic codebase mapping, but there's no detail on how context is auto-gathered (e.g., codebase indexing/@codebase) nor any independent/hands-on confirmation that it explains an unfamiliar codebase without manual file selection. Missing for 10: technical explanation of automatic context retrieval, independent user validation of whole-codebase explanation, and comparison to manual context selection workflows.
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
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”
Context management
developerHave the agent build and recall memory automatically across sessions
weight 2 · round drawnCursornone0/10No evidence describes persistent memory that automatically builds and recalls context across sessions; docs mention repo tracing, plan mode, and MCP integrations but nothing about cross-session memory recall.
Google Antigravitynone0/10The 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.”
developerInclude multiple project directories in a single session for broader context
weight 2 · round to Google AntigravityCursornone0/10No evidence in the pack mentions multi-root workspaces or including multiple project directories in a single Cursor session; docs cover repo navigation, MCP, agents, and integrations but not multi-directory context.
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.”
developerAdd a project instructions file to set coding standards and conventions the agent follows
weight 3 · round to Google AntigravityCursor's docs mention adding 'rules' as one of its features (alongside plugins, skills, MCPs) which aligns with the project-instructions concept, but the evidence pack gives no detail on how project rule files work, their scope, or how the agent applies them to enforce coding standards. missing for 10: documentation of the rules file format/location, examples of coding standards enforcement, independent confirmation the agent actually follows these instructions consistently.
- [claimed-docs] “Add plugins, skills, MCPs, and rules from one place”
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.”
Issue diagnosis
developerReproduce issues, narrow down root causes, and verify fixes
weight 3 · round drawncursor-docs-3 directly claims the exact capability ('Reproduce issues, narrow the root cause, and verify the fix'), and supporting docs on codebase tracing, diffs/checks, and agents running their own environments (cursor-docs-1, cursor-docs-4, cursor-docs-12) plausibly back this workflow. However, this is a first-party marketing/docs claim only, with no independent or hands-on corroboration of actual debugging workflows, and community evidence highlights general bugginess/quality concerns rather than validating this specific capability. Missing for 10: independent verification or hands-on case studies of reproduce/root-cause/verify-fix workflows, more detail on how reproduction (e.g., test running, log inspection) is concretely supported.
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
Ecosystem — integrations, plugins, and third-party ecosystem storiesEcosystem
Integrations, plugins, and third-party ecosystem stories
Marketplace
developerEquip the agent with custom skills to perform specialized tasks
weight 1 · round to Google AntigravityCursor's docs mention a marketplace to 'Add plugins, skills, MCPs, and rules from one place' and detailed MCP support (custom servers, marketplace install, enterprise controls), enabling developers to extend the agent with specialized tool integrations. However, there's no dedicated documentation on a 'skills' framework distinct from MCP/rules, no examples of custom skill creation workflow, and no independent/community corroboration of this specific capability. Missing for 10: detailed skills documentation/tutorial, examples of custom skill authoring, independent hands-on validation.
- [claimed-docs] “Add plugins, skills, MCPs, and rules from one place”
- [claimed-docs] “Model Context Protocol (MCP) enables Cursor to connect to external tools and data sources.”
- [claimed-docs] “Click "Add to Cursor" on a marketplace entry to install it and authenticate with OAuth.”
- [claimed-docs] “Configure custom MCP servers with a JSON file”
- [claimed-docs] “Enterprise admins can control which MCP servers users may run from the Cursor dashboard.”
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 …”
engineering-leadIntegrate third-party partner-built agent apps into my workflows
weight 1 · round to CursorCursor documents a marketplace for adding third-party plugins, skills, and MCP servers with OAuth authentication, plus native integrations with GitHub, GitLab, Slack, Linear, and more, letting teams plug partner-built tools/agents into their workflows, with enterprise admin controls over which servers are allowed. Missing for 10: independent/hands-on corroboration of using specific partner-built agent apps (vs. generic tool connectors) and clearer distinction between simple MCP data-tools and full third-party 'agent apps'.
- [claimed-docs] “Add plugins, skills, MCPs, and rules from one place”
- [claimed-docs] “Work with GitHub, GitLab, Azure DevOps, Bitbucket, JetBrains, Slack, Linear, and more”
- [claimed-docs] “Model Context Protocol (MCP) enables Cursor to connect to external tools and data sources.”
- [claimed-docs] “Click "Add to Cursor" on a marketplace entry to install it and authenticate with OAuth.”
- [claimed-docs] “Configure custom MCP servers with a JSON file”
- [claimed-docs] “Enterprise admins can control which MCP servers users may run from the Cursor dashboard.”
Google Antigravitydisputedcontradicted4/10Vendor 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,…”
Team knowledge
engineering-leadCreate a shared workspace from my docs and repos as a common source of truth for the team
weight 1 · round drawnCursornone0/10Evidence shows integrations (GitHub, Slack, Linear), MCP/plugins, and rules configuration, but nothing describes a dedicated 'shared workspace' feature that unifies docs and repos into a common team source of truth — this is a fair ask for a team-oriented dev tool but unaddressed in the pack.
Google Antigravitynone0/10Antigravity'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…”
Tool integration
developerConnect the agent to workflow tools like Jira, Slack, and Google Drive to extend its context
weight 3 · round to CursorCursor documents MCP support that connects to external tools/data sources, an MCP marketplace with OAuth install, and explicit integration with Slack alongside GitHub/GitLab/Linear/Jira-style trackers, plus Slack-based agent collaboration—covering the story's workflow-tool extension use case. Missing for 10: explicit first-party Jira/Google Drive connector documentation and independent hands-on verification of these integrations working end-to-end.
- [claimed-docs] “Model Context Protocol (MCP) enables Cursor to connect to external tools and data sources.”
- [claimed-docs] “Click "Add to Cursor" on a marketplace entry to install it and authenticate with OAuth.”
- [claimed-docs] “Configure custom MCP servers with a JSON file”
- [claimed-docs] “Work with GitHub, GitLab, Azure DevOps, Bitbucket, JetBrains, Slack, Linear, and more”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
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…”
developerKick off agent tasks directly from GitHub, GitLab, Linear, or Slack
weight 2 · round to CursorCursor's docs explicitly list integrations with GitHub, GitLab, Slack, and Linear, and describe agents that run on triggers/schedules and collaborate in Slack or review PRs in GitHub, supporting the story's core claim. However, there's no detailed first-party documentation of the exact trigger mechanics per platform (e.g., a Linear ticket auto-spawning an agent) nor independent/hands-on confirmation that this works reliably. Missing for 10: platform-specific trigger documentation for each of GitHub/GitLab/Linear/Slack, and independent verification of the workflow in practice.
- [claimed-docs] “Work with GitHub, GitLab, Azure DevOps, Bitbucket, JetBrains, Slack, Linear, and more”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
Ide terminal integration — meeting you in the IDE and terminal — extensions, inline flows, contextIde terminal integration
Meeting you in the IDE and terminal — extensions, inline flows, context
Cross device continuity
developerStart a task on one device and continue it later from another device or browser
weight 2 · round to Google AntigravityCursor's Background Agents run remotely and can be monitored/interacted with via terminal, Slack, and GitHub PRs, implying a task could be checked or continued from different surfaces, but there is no explicit documentation of resuming a specific in-progress task from a different device or browser session. Missing for 10: explicit cross-device/browser session handoff documentation, hands-on confirmation of resuming a task started elsewhere, and details on state syncing across clients.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
Ide integration
developerView interactive diffs and share selected code as context from within my JetBrains IDE
weight 1 · round drawnCursornone0/10The only evidence touching JetBrains is a single line listing JetBrains among integrations (cursor-docs-6), with no detail on interactive diffs or context-sharing features within a JetBrains IDE specifically. No documentation, screenshots, or community reports confirm this JetBrains-specific capability.
- [claimed-docs] “Work with GitHub, GitLab, Azure DevOps, Bitbucket, JetBrains, Slack, Linear, and more”
Google Antigravitynone0/10Antigravity 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…”
developerChat with the coding assistant directly inside my IDE for contextual help
weight 3 · round drawnCursor's docs describe an IDE-integrated assistant that traces repo structure, scopes changes via Plan Mode, reproduces issues, and hands off tasks while the developer reviews — all consistent with in-IDE contextual chat, and community commentary confirms it functions as a VS Code-based assistant with prompts/harness. missing for 10: no explicit citation naming a dedicated 'chat panel' UI or independent praise of chat quality/context-awareness specifically.
- [claimed-docs] “Trace how a repo fits together and find the right places to start”
- [claimed-docs] “Scope changes, use Plan Mode, and ship bigger work with confidence”
- [claimed-docs] “Reproduce issues, narrow the root cause, and verify the fix”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
- [community] “"Cursor is an extension for VS Code, a harness and a bunch of prompts. They have their own model (Composer 2) which is based on Kimi K2.5, b…”
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”
Session management
developerReview diffs visually and run multiple sessions side by side in a desktop app
weight 2 · round to Google AntigravityCursor's docs explicitly describe inspecting diffs before merge and launching fleets of agents to work in parallel, both core to a desktop IDE experience with visual diff review and concurrent sessions. Missing for 10: independent/hands-on confirmation of the side-by-side session UI and a detailed walkthrough of the diff viewer beyond marketing copy.
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
engineering-leadManage multiple agent-driven coding sessions from one unified workspace
weight 2 · round to Google AntigravityCursor's docs explicitly describe launching 'fleets of agents that work in parallel on ambitious tasks for hours or days' and setting up always-on agents on schedules/triggers, all accessible from Cursor's interface spanning terminal, Slack, and GitHub — directly matching a unified multi-session agent workspace for a lead overseeing parallel work. Missing for 10: independent/hands-on corroboration of the multi-agent dashboard UX, and no detail on cross-session visibility/coordination features specifically framed for engineering-lead oversight.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [claimed-docs] “Accelerate development by handing off tasks to Cursor, while you focus on making decisions.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
Terminal workflow
developerRun a coding agent locally from my terminal
weight 3 · round to Google AntigravityCursor ships an official CLI (cursor.com/cli) with a documented install command (curl ... | bash) and docs explicitly state 'Cursor runs in your terminal', confirming a local terminal-based agent capability alongside its IDE. Missing for 10: independent/hands-on verification of terminal agent usage and deeper CLI usage documentation beyond the install step.
- [probe] “official CLI documented at https://cursor.com/cli”
- [claimed-docs] “curl https://cursor.com/install -fsS | bash”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
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 …”
developerRun the agent non-interactively in scripts for workflow automation
weight 2 · round to Google AntigravityCursor ships an official CLI (cursor-probe-1, cursor-docs-14) and documents 'always-on agents that run on schedules or triggers to build, maintain, and fix your software' (cursor-docs-9), which implies non-interactive/automated agent execution suitable for scripts/CI. However, there is no concrete documentation of CLI flags, headless/print modes, exit codes, or scripting examples, nor independent hands-on confirmation of this workflow. Missing for 10: explicit CLI non-interactive flag/usage docs, examples of piping/scripting the agent, and independent verification that scheduled/triggered agents work as scripted automation.
- [probe] “official CLI documented at https://cursor.com/cli”
- [claimed-docs] “curl https://cursor.com/install -fsS | bash”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
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.”
Openness — open source, data portability, and self-hosting storiesOpenness
Open source, data portability, and self-hosting stories
ai-native userDo everything through the API that I can do in the UI
weight 2 · round to Google AntigravityCursornone0/10The evidence pack shows no public API for Cursor; it mentions an official CLI and MCP (for connecting external tools INTO Cursor), but nothing about a programmatic interface exposing Cursor's own UI capabilities (agents, plan mode, review, etc.) for external control.
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…”
ai-native userExport all of my data in open formats and leave
weight 3 · round drawnCursornone0/10No evidence in the pack addresses data export, portability, or open-format data extraction from Cursor; being built on VS Code (a fork) doesn't itself guarantee user data/settings export tooling is documented anywhere here.
ai-native userRead the product's source under an open license
weight 2 · round drawnCursornone0/10Cursor is known to be closed-source (a proprietary VS Code fork), and the evidence pack contains no mention of any open-source license or public repository for Cursor's source code; all references are to product docs, features, or community complaints unrelated to licensing.
Google Antigravitynone0/10No 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.
Pricing limits — free-tier ceilings, usage caps, and rate limits before you have to payPricing limits
Free-tier ceilings, usage caps, and rate limits before you have to pay
Authentication
developerAuthenticate with an API key instead of an account login
weight 2 · round drawnCursornone0/10No evidence in the pack describes API key authentication as an alternative to account login for Cursor; docs reference OAuth-based MCP authentication and account-based login flows only.
Google Antigravitynone0/10Evidence 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…”
engineering-leadAuthenticate through an enterprise identity or cloud platform for compliance and scalability
weight 2 · round drawnCursornone0/10The evidence pack shows Cursor has enterprise admin controls for MCP servers but contains no evidence of SSO/SAML integration, enterprise identity provider authentication (e.g., Okta, Azure AD, Google Workspace), or cloud platform login for compliance purposes. This is a fair and applicable axis for a widely-adopted dev tool sold to enterprises, so absence of evidence yields 'none' rather than 'na'.
- [claimed-docs] “Enterprise admins can control which MCP servers users may run from the Cursor dashboard.”
Google Antigravitynone0/10No 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…”
developerSign in with my existing product subscription plan to use the coding agent
weight 2 · round drawnCursornone0/10The evidence pack describes Cursor's agent features, MCP integrations, and installation steps, but contains no documentation or confirmation that users authenticate with an existing subscription plan to access the coding agent (only tangential community chatter about login policy hallucinations). Missing for 10: explicit account/subscription sign-in flow docs, plan-tier access confirmation, and any first-party statement linking subscription plan to agent usage.
- [community] “Cursor's AI support agent hallucinated a single-device login policy, telling a user this was intentional. A Cursor developer later clarified…”
Google Antigravitynone0/10No 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…”
developerSign in with a personal account to get free-tier access without managing API keys
weight 1 · round to Google AntigravityCursornone0/10The evidence pack contains no documentation or first-party description of a sign-in flow that grants free-tier access without requiring API keys; only tangential community mentions of account workarounds for usage limits exist. Missing for 10: any docs on account creation/sign-in, free-tier terms, or explicit no-API-key requirement.
- [community] “Cursor is caught in a cat-and-mouse game against workarounds where users create new accounts to get unlimited use; a repo enabling this (cur…”
Google Antigravitydisputedcontradicted3/10Vendor 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”
Model choice
developerLet the tool automatically pick the best model for each task
weight 1 · round drawnCursornone0/10The evidence shows Cursor lets developers manually choose among multiple models (OpenAI, Anthropic, Gemini, etc.) but nothing indicates an automatic 'best model for the task' selection feature. missing for 10: any documentation or claim of an auto-select/router feature that picks models per task, evidence of cost/performance-based automatic routing.
- [claimed-docs] “Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, SpaceXAI, and Cursor.”
Google Antigravitynone0/10Docs 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”
developerChoose which underlying AI model powers my session from multiple providers
weight 2 · round drawncursor-docs-7 confirms Cursor lets developers choose between models from multiple providers (OpenAI, Anthropic, Gemini, and Cursor's own), directly matching the story. Missing for 10: independent hands-on verification of per-session model switching UI/behavior and pricing implications tied to model choice.
- [claimed-docs] “Choose between every cutting-edge model from OpenAI, Anthropic, Gemini, SpaceXAI, and Cursor.”
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.”
Privacy posture — data-handling and privacy storiesPrivacy posture
Data-handling and privacy stories
ai-native userChoose where my data is stored (region/residency)
weight 2 · round drawnCursornone0/10No evidence in the pack mentions data residency, region selection, or storage location controls for Cursor; the docs snippets cover agents, MCP, and integrations but nothing about choosing data storage region. Missing for 10: any mention of regional data residency options, enterprise data location controls, or compliance documentation addressing storage jurisdiction.
Google Antigravitynone0/10No 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.
ai-native userPrevent my data from being used to train AI models
weight 3 · round to Google AntigravityCursornone0/10The evidence pack contains no documentation of a privacy mode, opt-out of training, or data-retention controls for Cursor; all cited docs cover unrelated features (agents, MCP, integrations) and community threads are unrelated to training-data privacy.
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)”
ai-native userControl data retention and deletion
weight 2 · round to Google AntigravityCursornone0/10The evidence pack contains no documentation of data retention settings, deletion controls, privacy dashboard, or data handling policies for Cursor; only unrelated docs on features (MCP, agents, integrations) and community complaints about bugs/pricing are present. Missing for 10: any first-party privacy policy docs, retention period settings, data deletion request mechanism, or enterprise data controls.
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)”
ai-native userOpt out of telemetry and usage tracking
weight 2 · round to Google AntigravityCursornone0/10The evidence pack contains no mention of telemetry settings, privacy controls, or usage-tracking opt-out mechanisms; docs only cover unrelated features like MCP, agents, and integrations. Missing for 10: any privacy policy or settings documentation, telemetry opt-out toggle, or usage data collection disclosure.
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)”
Review safety — keeping generated changes safe — diffs, approvals, guardrailsReview safety
Keeping generated changes safe — diffs, approvals, guardrails
Data governance
engineering-leadOpt out of having my code and prompts used for AI model training
weight 1 · round to Google AntigravityCursornone0/10The evidence pack contains no mention of privacy settings, opt-out of training, or data usage policies for Cursor; all docs entries relate to unrelated features (agents, MCP, integrations) and community items focus on bugs/pricing/model sourcing, not training data controls.
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)”
Pr review
developerHave the agent stage changes, write commit messages, create branches, and open pull requests
weight 3 · round to CursorDocs show GitHub/GitLab integration and agents that build/test/demo work end-to-end for review (cursor-docs-6, cursor-docs-10, cursor-docs-12), implying some git-workflow automation, but there's no explicit documentation of the agent staging changes, writing commit messages, creating branches, or opening pull requests. missing for 10: explicit commit-message generation, branch creation, PR-opening workflow documentation, and any hands-on confirmation these steps work end-to-end.
- [claimed-docs] “Work with GitHub, GitLab, Azure DevOps, Bitbucket, JetBrains, Slack, Linear, and more”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
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.”
developerGet automatic code review with contextual feedback on every pull request
weight 3 · round to CursorCursor's docs explicitly claim it 'reviews PRs in GitHub' and can 'inspect diffs, run checks, and catch problems before you merge,' directly matching automated PR review with contextual feedback, backed by GitHub/GitLab/Bitbucket integration claims. missing for 10: independent/hands-on verification of review quality, details on triggering on every PR automatically, and no community corroboration of this specific feature.
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
- [claimed-docs] “Work with GitHub, GitLab, Azure DevOps, Bitbucket, JetBrains, Slack, Linear, and more”
Google Antigravitynone0/10Antigravity 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.”
developerInspect diffs and run checks to catch problems before merging
weight 3 · round to Google Antigravitycursor-docs-4 explicitly claims the capability ('Inspect diffs, run checks, and catch problems before you merge') and cursor-docs-10/12 support a broader PR review workflow, but there is no independent or hands-on corroboration of diff inspection or check-running in practice, and community evidence focuses on unrelated bugs/pricing rather than this feature. missing for 10: independent verification of diff review UI, details on what 'checks' run (tests/linters/CI), and hands-on confirmation of pre-merge workflow.
- [claimed-docs] “Inspect diffs, run checks, and catch problems before you merge”
- [claimed-docs] “Cursor runs in your terminal, collaborates in Slack, and reviews PRs in GitHub.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
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…”
Safe execution
engineering-leadControl which external tools and integrations the agent is allowed to access
weight 2 · round to CursorDocs show enterprise admins can restrict which MCP servers users may run from the Cursor dashboard, and users can toggle individual servers on/off, giving engineering leads direct control over external tool/integration access. Missing for 10: independent/hands-on corroboration of the admin dashboard controls and finer-grained per-tool permission examples beyond MCP servers.
- [claimed-docs] “Enterprise admins can control which MCP servers users may run from the Cursor dashboard.”
- [claimed-docs] “Toggle servers on/off without removing them”
- [claimed-docs] “Model Context Protocol (MCP) enables Cursor to connect to external tools and data sources.”
- [claimed-docs] “Configure custom MCP servers with a JSON file”
Google Antigravitydisputedcontradicted5/10Antigravity 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'…”
engineering-leadHave the agent operate inside a sandbox when interacting with code, tools, and network resources
weight 2 · round to Google AntigravityCursornone0/10The evidence pack contains no mention of sandboxing, isolated execution environments, or network/tool restriction controls for the agent; docs describe agents using 'their own computers' but give no detail on containment/sandboxing mechanisms. Missing for 10: any documentation of a sandbox/isolation feature, network egress controls, or filesystem restriction for agent actions.
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
Google Antigravitydisputedcontradicted4/10Antigravity 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…”
Security checks
engineering-leadSee license and public-code matching references for AI-suggested code
weight 1 · round drawnCursornone0/10No evidence anywhere in the pack mentions license detection, public code matching, provenance references, or IP attribution for AI-suggested code; docs focus on repo navigation, diffs, agents, and integrations, none of which addresses license/code-match transparency.
Google Antigravitynone0/10No 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.
developerGet contextual explanations and automatic fixes for security vulnerabilities
weight 2 · round drawnCursornone0/10The evidence pack shows general code review/diff-inspection features (cursor-docs-4) and broad agent capabilities, but nothing specifically documents contextual security vulnerability explanations or automated security fixes. Missing for 10: any mention of vulnerability detection, security scanning integration, or CVE/security-specific fix suggestions.
Google Antigravitynone0/10No 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.
Not comparable on these axes
ai-native userConnect an agent via an official MCP server
weight 3 · not comparableCursorn/aCursor is itself an AI coding agent; the evidence (cursor-docs-15 to cursor-docs-19) shows Cursor acting as an MCP client that connects to external MCP servers, not Cursor exposing an official MCP server for other agents to connect to. Per the agent-role exception, client-side MCP support does not make this server-side story applicable.
Google Antigravityn/aAntigravity is itself an agentic coding product (IDE/CLI/SDK) that acts as an MCP client—connecting to external MCP servers for tools/context (antigravity-docs-12, antigravity-docs-14, antigravity-docs-22, antigravity-docs-43)—rather than exposing itself as an MCP server for other agents to connect to. Per the agent-role exception, this axis (serving an official MCP server) does not apply to a product that is itself the agent/client.
- [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] “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”
ai-native userExplore an interactive API reference with runnable examples
weight 2 · not comparableCursornone0/10No evidence of an interactive API reference with runnable examples for Cursor; docs entries describe product features and MCP setup but nothing about an API reference or executable code samples.
Google Antigravityn/aAntigravity is an agentic coding IDE/CLI/SDK product, not an API/SaaS service exposing a public API surface meant for interactive exploration; the probe explicitly found no OpenAPI spec. An interactive API reference with runnable examples is not a fair axis for this kind of developer tool.
- [probe] “PROBE openapi: all candidate paths 404 (https://antigravity.google/openapi.json, https://antigravity.google/swagger.json, https://antigravit…”
ai-native userTest against a sandbox environment without touching production data
weight 1 · not comparableCursorn/aSandbox testing environments vs production data isolation is a data/infrastructure axis relevant to backend/platform products, not to an AI coding assistant like Cursor, which operates on local/repo code rather than managing production data environments.
Google Antigravitydisputedcontradicted4/10Antigravity'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…”
developerConfigure a reproducible cloud environment with the dependencies and setup steps my repository needs
weight 2 · not comparableCursor's docs mention cloud/background agents that 'use their own computers to build, test, and demo features' and can be launched in fleets or run on schedules, implying some cloud execution environment, but there's no evidence pack detail on how a developer configures dependencies, install scripts, or a reproducible environment spec (e.g. Dockerfile/environment.json) for these agents. Missing for 10: explicit documentation of environment configuration format, dependency/setup step definition, and evidence of reproducibility across runs.
- [claimed-docs] “Launch fleets of agents that work in parallel on ambitious tasks for hours or days.”
- [claimed-docs] “Set up always-on agents that run on schedules or triggers to build, maintain, and fix your software.”
- [claimed-docs] “Agents use their own computers to build, test, and demo features end to end for you to review.”
Google Antigravityn/aAntigravity is a local IDE/CLI/agent orchestration tool operating on a developer's own machine (or remote desktop sessions), not a cloud environment provisioning/dev-container service; there is no evidence of configuring reproducible cloud sandboxes with dependency/setup steps tied to a repo. This axis is a category error for this product type.
ai-native userSelf-host the core product
weight 3 · not comparableCursorn/aCursor is a proprietary AI coding assistant/IDE fork product, not an open-source or self-hostable platform; self-hosting the core product is a category error for this type of closed commercial tool.
Google Antigravitynone0/10No 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…”