cnoe-io/ai-platform-engineering - Open Source PR Review Scorecard

CAIPE: Community AI Platform Engineering

C-Rank Grade: A (Welcoming) - 60/100

External PR Merge Rate: 56%

Response Time: 21h

First Timer Success: 50%

Frequently Asked Questions

Is cnoe-io/ai-platform-engineering welcoming to first-time open-source contributors?

cnoe-io/ai-platform-engineering has a recorded first-timer success rate of 50.0%. 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 cnoe-io/ai-platform-engineering respond to incoming external pull requests in approximately 20.7 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 60.5 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 60.5 places cnoe-io/ai-platform-engineering in the A tier.

What is the external contributor pull request merge rate for cnoe-io/ai-platform-engineering?

The external contributor pull request merge rate for cnoe-io/ai-platform-engineering is 55.8%, based on public PR activity from non-core contributors.

Are there Good First Issues available in cnoe-io/ai-platform-engineering?

cnoe-io/ai-platform-engineering does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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cnoe-io/ai-platform-engineering

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CAIPE: Community AI Platform Engineering

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AI Maintainer Review Guidelines

Review Persona

Active Open-Source Maintainer

Warmth Score
7.8/10
Patience Score
8.2/10
Nitpick Rate
20%

Growing TypeScript project in cnoe-io/ai-platform-engineering welcoming community pull requests and bug fixes.

Top PR Submission Do's

  • •Ensure code complies with TypeScript style conventions
  • •Keep PRs scoped and well-documented
  • •Include relevant test coverage for changes

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit unlinked PRs without context
  • •Do not break existing automated test suites
  • •Do not mix unrelated refactors with feature work
Response Velocity
20 hours
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
55.8%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
50.0%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
7 core
Highly collaborative maintainer core
Diagnostic Health HUD
55.8%
Merge Gauge
50.0%
1st-Timer
Community Vibe52/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for cnoe-io/ai-platform-engineering
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/cnoe-io/ai-platform-engineering)](https://getmerged.abhishekco.de/cnoe-io/ai-platform-engineering?utm_source=github&utm_medium=badge)

Active Good First Issues (1)

View on GitHub

Description While actively editing a skill or agent file in the UI, the session can unexpectedly refresh — even during active typing — causing all unsaved changes to be lost. The refresh does not appear to be tied to a specific idle timeout; it can happen during active use, not necessarily after a long period of inactivity. Steps to Reproduce Open the UI and start editing a skill or agent file Type actively without saving Observe that the UI may unexpectedly refresh Unsaved changes are lost Expected Behavior The UI should not auto-refresh during active editing sessions, or should at minimum warn the user / prompt to save before discarding unsaved changes. Actual Behavior The UI silently refreshes and all unsaved changes are lost. This can happen during active use, not just after long idle periods. Impact Users are losing work unexpectedly. A workaround of saving very frequently is required, which is not ideal UX. Additional Context Reported via internal service desk (OPENSD-2417

📅 Opened Jul 9, 2026💬 0 comments
Quality: 50/100Contribute
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Contributor Compatibility & Review Speed Analysis for cnoe-io/ai-platform-engineering

When evaluating whether to contribute to cnoe-io/ai-platform-engineering, 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 cnoe-io/ai-platform-engineering acknowledge new external contributions in approximately 20 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 55.8% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to cnoe-io/ai-platform-engineering

01

Is cnoe-io/ai-platform-engineering welcoming to first-time open-source contributors?

cnoe-io/ai-platform-engineering has a recorded first-timer success rate of 50.0%. 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 ~20 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 60.5 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 60.5 places cnoe-io/ai-platform-engineering in the Welcoming tier.

04

What is the external contributor pull request merge rate for cnoe-io/ai-platform-engineering?

The external pull request merge rate is 55.8%. 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 cnoe-io/ai-platform-engineering?

cnoe-io/ai-platform-engineering does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for cnoe-io/ai-platform-engineering 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.