Complete AI development workflow for 19+ tools. Builtin rules, agents, and conventions out of the box. Generate native configs for Claude, Cursor, Copilot, Windsurf, Gemini, Codex and more.
C-Rank Grade: A (Welcoming) - 61/100
External PR Merge Rate: 64%
Response Time: <1h
First Timer Success: 100%
Goldziher/ai-rulez has a recorded first-timer success rate of 100.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in Goldziher/ai-rulez respond to incoming external pull requests in approximately 0.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 61.1 places Goldziher/ai-rulez in the A tier.
The external contributor pull request merge rate for Goldziher/ai-rulez is 63.6%, based on public PR activity from non-core contributors.
Goldziher/ai-rulez does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Growing Go project in Goldziher/ai-rulez welcoming community pull requests and bug fixes.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/Goldziher/ai-rulez?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
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90% receive response in
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 06:00 UTC (06:00 UTC in your timezone). Recommended submission window is Wednesday - Friday from 04:00 to 08:00 UTC (04:00 - 08:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~4 hours (80% approval). Large PRs (>500 lines) take ~0 hours (29% approval). Keep your diff compact for rapid review.
Needs repository admin rights. Draft values are in docs/maintainers/github-metadata.md (description, homepage, 18 topics, gh repo edit command, release notes template). After the v5 release, check the npm, PyPI, Homebrew and Docker pages render the new positioning. Related: #282.
APM and Tessl import are only covered by synthetic fixtures. Add one real-world project of each (licence permitting) under tests/fixtures, with import + generate golden tests, and note the source and commit in the fixture README. Related: #288.
Never run live, by design: they need a real identity. Keyless Sigstore sign + verify against staging with a real OIDC identity (internal/signing/sigstore); record the transcript and certificate identity policy used KMS key-URI sign + verify with a real key (AWS/GCP/Azure/Vault as supported) Add the results to docs/signing.md and wire a manual workflow_dispatch job so it can be rerun before releases Offline coverage already exists via the fake Sigstore backend and the verify-only split. Related: #288, #290.
Everything below is implemented and offline-tested, but needs a real provider key to prove. Run with AI_RULEZ_LIVE_LLM=1 and a Gemini key (and Anthropic/OpenAI keys for the rest): TestLiveThinkingTokensAreCharged: both backends settle on the provider's total_tokens for gemini/, google_ai/ and vertex_ai/ (liter-llm 2.2.0 maps thoughtsTokenCount; the Go module carries no mapping code, so only a live call proves it) RV-LLM-1 and RV-LLM-3 reproductions from #287 Anthropic cache-read/write accounting and OpenAI reasoning-model max_tokens behaviour (liter-llm #255, #264) Record the results (model, date, usage vs billed) in docs/llm.md and close #287's live items Why it is not done in-repo: no provider credentials are available to the automated work. Related: #287, liter-llm tracking issue xberg-io/liter-llm#269.
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When evaluating whether to contribute to Goldziher/ai-rulez, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of Goldziher/ai-rulez acknowledge new external contributions in approximately <1 hour. Out of all submitted pull requests from non-core authors in the last 180-day window, 63.6% were successfully merged into the primary branch.
Goldziher/ai-rulez has a recorded first-timer success rate of 100.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~<1 hour. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 61.1 places Goldziher/ai-rulez in the Welcoming tier.
The external pull request merge rate is 63.6%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Goldziher/ai-rulez does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for Goldziher/ai-rulez are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.