Gentleman-Programming/gentle-ai - Open Source PR Review Scorecard

Gentle-AI configures the AI coding agents you already use: Claude Code, Cursor, OpenCode, Codex, Pi, and more. Choose persistent memory, Organic-Driven Development, curated skills, MCP servers, personas, and optional bounded review. Open source, no agent lock-in.

C-Rank Grade: A (Welcoming) - 69/100

External PR Merge Rate: 53%

Response Time: 18h

First Timer Success: 12%

Frequently Asked Questions

Is Gentleman-Programming/gentle-ai welcoming to first-time open-source contributors?

Gentleman-Programming/gentle-ai has a recorded first-timer success rate of 11.6%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in Gentleman-Programming/gentle-ai respond to incoming external pull requests in approximately 17.9 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 68.6 C-Rank™ score (A Tier) represent?

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 68.6 places Gentleman-Programming/gentle-ai in the A tier.

What is the external contributor pull request merge rate for Gentleman-Programming/gentle-ai?

The external contributor pull request merge rate for Gentleman-Programming/gentle-ai is 53.5%, based on public PR activity from non-core contributors.

Are there Good First Issues available in Gentleman-Programming/gentle-ai?

Gentleman-Programming/gentle-ai currently has 16 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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Gentle-AI configures the AI coding agents you already use: Claude Code, Cursor, OpenCode, Codex, Pi, and more. Choose persistent memory, Organic-Driven Development, curated skills, MCP servers, personas, and optional bounded review. Open source, no agent lock-in.

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AI Maintainer Review Guidelines

Review Persona

Strict Quality Architect

Warmth Score
6.6/10
Patience Score
7.2/10
Nitpick Rate
43%

Rigorous architecture standards (66% critical review signals). Ensure PRs strictly follow guidelines before requesting review in Gentleman-Programming/gentle-ai.

Top PR Submission Do's

  • •Add unit tests with >80% coverage for modified code paths
  • •Run repository linter and code formatters locally before pushing
  • •Link relevant GitHub issue ID in PR description pre-flight checklist

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without referencing an existing issue
  • •Do not mix refactoring and feature logic into a single commit
  • •Do not ping maintainers repeatedly within 24 hours of opening
Response Velocity
17 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
53.5%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
11.6%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
752 core
Highly collaborative maintainer core
Diagnostic Health HUD
53.5%
Merge Gauge
11.6%
1st-Timer
Community Vibe41/100

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Active Good First Issues (5)

View on GitHub

Pre-flight Checklist I have searched existing issues and this is not a duplicate I understand that PRs will be rejected if the linked issue does not have status:approved 🔍 Affected Area Documentation 💡 Problem Statement Parent tracker #504 intends to install 11 native GitHub Copilot phase agents under ~/.copilot/agents/, preferably as thin wrappers around the SDD skills already installed under ~/.copilot/skills/. The repository does not yet have organic runtime evidence that one wrapper contract works on both the current stable Windows runtime and a current stable POSIX runtime. Without that evidence, activating production assets would guess at file discovery, frontmatter selectors, skill resolution, delegation, and caller-model inheritance. This issue must establish the wrapper contract before any production capability or asset activation. 📦 Proposed Solution Create a focused, sanitized runtime-proof report for one candidate thin-wrapper format. Test the exact same candid

📅 Opened Sep 4, 2026💬 1 comment
Quality: 100/100Contribute

Pre-flight Checklist I have searched existing issues and this is not a duplicate I understand that PRs will be rejected if the linked issue does not have status:approved 📝 Bug Description In Gentle AI v2.5.0, the canonical sdd-apply skill contains separate model-capable and model-small sections. The model-capable section explicitly includes: Apply any `rules.apply` from `openspec/config.yaml` However, the model-small section contains no equivalent instruction. Consequently, an sdd-apply skill rendered for a small-model profile is not explicitly required to apply the project's phase-specific rules.apply instructions. This is related to, but distinct from, #4114: #4114: sdd-verify omits rules.verify from both model tiers. This issue: sdd-apply includes rules.apply in model-capable but omits it from model-small. 🔄 Steps to Reproduce Check out Gentle AI v2.5.0. Open: internal/assets/skills/sdd-apply/SKILL.md Search for the model-section markers and rules.apply: rg -n '<

📅 Opened Sep 3, 2026💬 1 comment
Quality: 85/100Contribute

Pre-flight Checklist I have searched existing issues and this is not a duplicate I understand that PRs will be rejected if the linked issue does not have status:approved 📝 Bug Description TestInjectClaudeWorkspaceIsDiscoveredByNativeClaudeMCPList (internal/components/mcp/inject_test.go) fails against Claude Code CLI 2.1.114. The test injects a Claude workspace with a user-scope context7 server and an unapproved project-scope server, runs the real claude mcp list inside the workspace, and asserts the output contains both context7 and pending/approval wording for the project server. With CLI 2.1.114 the context7 half passes (reported as connected) but the unapproved project server is never mentioned, so the second assertion fails. This needs triage between two possible roots: (a) the CLI's mcp list reporting contract changed — unapproved project servers are no longer listed with that wording — so the test is version-fragile and should pin to documented CLI behavior or gate on

📅 Opened Aug 31, 2026💬 2 comments
Quality: 50/100Contribute

Pre-flight Checklist I have searched existing issues and this is not a duplicate I understand that PRs will be rejected if the linked issue does not have status:approved 📝 Bug Description The gentle-ai:codegraph-guidance block injected into agent configs instructs agents to create Git worktrees "under the user's home directory, preferably as a sibling such as <repo-parent>/<repo-name>-worktrees/<worktree-name>". For nested project layouts (e.g. ~/Projects/<lang>/<repo>), <repo-parent> is undefined: it can be read as the immediate parent of the repository root (~/Projects/<lang>) or as the user's projects root (~/Projects). The word "preferably" makes the rule advisory, so different agent sessions resolve the placeholder differently. Verified on installed 2.5.0-rc.2 and on current main (internal/components/communitytool/codegraph_guidance.go — identical wording). 🔄 Steps to Reproduce Install gentle-ai with CodeGraph guidance injected into agent configs (OpenCode/Pi). Have a

📅 Opened Aug 30, 2026💬 2 comments
Quality: 65/100Contribute

Pre-flight Checklist I have searched existing issues and this is not a duplicate I understand that PRs will be rejected if the linked issue does not have status:approved 📝 Bug Description skills/gentle-ai-collab-perfect/SKILL.md teaches contributors to recount GitHub pull-request scope with: git diff --stat <base>..<head> That two-dot comparison compares the endpoint trees. When the base advances independently, it includes upstream-only changes as reverse deletions or modifications and therefore inflates or misrepresents the changes introduced by the pull request. GitHub pull-request scope is merge-base based. The contributor guidance should use: git diff --stat <base>...<head> or an explicit merge-base comparison that preserves <head> as the compared side. This is a contributor-facing documentation defect, independent of the implementation of native review authority. 🔄 Steps to Reproduce Check out the current main branch. Inspect skills/gentle-ai-collab-perfect/SKILL.md

📅 Opened Aug 26, 2026💬 1 comment
Quality: 50/100Contribute
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Contributor Compatibility & Review Speed Analysis for Gentleman-Programming/gentle-ai

When evaluating whether to contribute to Gentleman-Programming/gentle-ai, 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 Gentleman-Programming/gentle-ai acknowledge new external contributions in approximately 17 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 53.5% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to Gentleman-Programming/gentle-ai

01

Is Gentleman-Programming/gentle-ai welcoming to first-time open-source contributors?

Gentleman-Programming/gentle-ai has a recorded first-timer success rate of 11.6%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~17 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 68.6 C-Rank™ score represent?

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 68.6 places Gentleman-Programming/gentle-ai in the Welcoming tier.

04

What is the external contributor pull request merge rate for Gentleman-Programming/gentle-ai?

The external pull request merge rate is 53.5%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in Gentleman-Programming/gentle-ai?

Yes, Gentleman-Programming/gentle-ai currently has 16 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for Gentleman-Programming/gentle-ai 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.