kitops-ml/kitops - Open Source PR Review Scorecard

An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI Artifact.

C-Rank Grade: A (Welcoming) - 61/100

External PR Merge Rate: 80%

Response Time: 21h

First Timer Success: 75%

Frequently Asked Questions

Is kitops-ml/kitops welcoming to first-time open-source contributors?

kitops-ml/kitops has a recorded first-timer success rate of 75.0%. 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 kitops-ml/kitops respond to incoming external pull requests in approximately 21.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 60.6 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 60.6 places kitops-ml/kitops in the A tier.

What is the external contributor pull request merge rate for kitops-ml/kitops?

The external contributor pull request merge rate for kitops-ml/kitops is 79.5%, based on public PR activity from non-core contributors.

Are there Good First Issues available in kitops-ml/kitops?

kitops-ml/kitops does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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kitops-ml/kitops

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An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI Artifact.

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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 kitops-ml/kitops.

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
20 hours
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
79.5%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
75.0%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
14 core
Highly collaborative maintainer core
Diagnostic Health HUD
79.5%
Merge Gauge
75.0%
1st-Timer
Community Vibe69/100

Embed C-Rank Badge

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

GetMerged C-Rank badge for kitops-ml/kitops
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/kitops-ml/kitops)](https://getmerged.abhishekco.de/kitops-ml/kitops?utm_source=github&utm_medium=badge)

Active Good First Issues (1)

View on GitHub

Problem Coding agents (Claude Code, Codex, Cursor, Copilot, Gemini CLI) increasingly drive CLIs directly. Today an agent's only way to learn kit is --help output, which is flag-oriented and says nothing about workflows: Kitfile authoring, pack/push/pull/unpack, tagging. Users who want agents working with ModelKits hand-write AGENTS.md sections or paste docs into context, and those drift from the installed kit version. Other agent-facing CLIs have converged on shipping this knowledge as an installable skill following the Agent Skills spec: hunk ships skills/hunk-review/SKILL.md in-repo and provides a hunk skill command to locate/load it beads has bd setup <agent> to install a skill and agent instructions, plus bd prime to print workflow context on demand Proposal Add a kit skill command that installs a SKILL.md (covering Kitfile authoring, the pack/push/pull/unpack workflow, tagging, and common errors) into the appropriate agent directory (.claude/skills/, the shared .agents/skills/,

📅 Opened Jul 18, 2026💬 0 comments
Quality: 90/100Contribute
Looking for more Go beginner tasks?Explore Go GFI

Contributor Community Vibe Feedback

Rate what actually matters after opening a pull request here.

Have you contributed to this repo?

Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.

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Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for kitops-ml/kitops

When evaluating whether to contribute to kitops-ml/kitops, 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 kitops-ml/kitops acknowledge new external contributions in approximately 20 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 79.5% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to kitops-ml/kitops

01

Is kitops-ml/kitops welcoming to first-time open-source contributors?

kitops-ml/kitops has a recorded first-timer success rate of 75.0%. 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 60.6 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 60.6 places kitops-ml/kitops in the Welcoming tier.

04

What is the external contributor pull request merge rate for kitops-ml/kitops?

The external pull request merge rate is 79.5%. 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 kitops-ml/kitops?

kitops-ml/kitops 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 kitops-ml/kitops 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.