Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
C-Rank Grade: B (Solid) - 48/100
External PR Merge Rate: 28%
Response Time: 8d
First Timer Success: 25%
shareAI-lab/learn-claude-code has a recorded first-timer success rate of 25.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in shareAI-lab/learn-claude-code respond to incoming external pull requests in approximately 188.9 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 47.6 places shareAI-lab/learn-claude-code in the B tier.
The external contributor pull request merge rate for shareAI-lab/learn-claude-code is 27.8%, based on public PR activity from non-core contributors.
shareAI-lab/learn-claude-code currently has 1 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Balanced & professional review environment in shareAI-lab/learn-claude-code. Maintains strict focus on technical quality and test standards.
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/shareAI-lab/learn-claude-code?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 14:00 UTC (14:00 UTC in your timezone). Recommended submission window is Monday - Wednesday from 12:00 to 16:00 UTC (12:00 - 16:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~123 hours (35% approval). Large PRs (>500 lines) take ~907 hours (15% approval). Keep your diff compact for rapid review.
Hi shareAI-lab team, I’ve been studying this repo and sketched a visual summary of how I understand the agent harness architecture. The diagram connects several concepts from the course, including system prompt assembly, memory, auto-compaction, permissions/hooks, background tasks, cron scheduling, task systems, subagents, agent teams, and worktree isolation. I’m sharing it in case it is useful for the docs or for other learners. Happy to revise it if any part does not match the intended architecture. Thanks for creating this repo. It helped me think more clearly about agent harness engineering.
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When evaluating whether to contribute to shareAI-lab/learn-claude-code, 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 shareAI-lab/learn-claude-code acknowledge new external contributions in approximately 7 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 27.8% were successfully merged into the primary branch.
shareAI-lab/learn-claude-code has a recorded first-timer success rate of 25.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~7 days+. 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 47.6 places shareAI-lab/learn-claude-code in the Solid tier.
The external pull request merge rate is 27.8%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, shareAI-lab/learn-claude-code currently has 1 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for shareAI-lab/learn-claude-code 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.