DaoCloud/public-image-mirror - Open Source PR Review Scorecard

很多镜像都在国外。比如 gcr 。国内下载很慢,需要加速。致力于提供连接全世界的稳定可靠安全的容器镜像服务。

C-Rank Grade: B (Solid) - 54/100

External PR Merge Rate: 78%

Response Time: 6d

First Timer Success: 78%

Frequently Asked Questions

Is DaoCloud/public-image-mirror welcoming to first-time open-source contributors?

DaoCloud/public-image-mirror has a recorded first-timer success rate of 77.8%. Repositories ranked B 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 DaoCloud/public-image-mirror respond to incoming external pull requests in approximately 153.6 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 53.7 C-Rank™ score (B 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 53.7 places DaoCloud/public-image-mirror in the B tier.

What is the external contributor pull request merge rate for DaoCloud/public-image-mirror?

The external contributor pull request merge rate for DaoCloud/public-image-mirror is 78.2%, based on public PR activity from non-core contributors.

Are there Good First Issues available in DaoCloud/public-image-mirror?

DaoCloud/public-image-mirror does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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DaoCloud/public-image-mirror

14,975
BSolid(54/100)Shell

很多镜像都在国外。比如 gcr 。国内下载很慢,需要加速。致力于提供连接全世界的稳定可靠安全的容器镜像服务。

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AI Maintainer Review Guidelines

Review Persona

High-Friction Gatekeeper

Warmth Score
5.0/10
Patience Score
6.0/10
Nitpick Rate
65%

Rigorous architecture standards (100% critical review signals). Ensure PRs strictly follow guidelines before requesting review in DaoCloud/public-image-mirror.

Top PR Submission Do's

  • Verify all existing package test suites run cleanly
  • Use conventional commit messages and clean branch names
  • 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
6 days+
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
78.2%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
77.8%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
2 core
Small core review team
Diagnostic Health HUD
78.2%
Merge Gauge
77.8%
1st-Timer
Community Vibe55/100

Embed C-Rank Badge

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

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

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for DaoCloud/public-image-mirror.

View all good first issues directly on GitHub

Looking for more Shell beginner tasks?Explore Shell 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.

3 ratings required
Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for DaoCloud/public-image-mirror

When evaluating whether to contribute to DaoCloud/public-image-mirror, 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 DaoCloud/public-image-mirror acknowledge new external contributions in approximately 6 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 78.2% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to DaoCloud/public-image-mirror

01

Is DaoCloud/public-image-mirror welcoming to first-time open-source contributors?

DaoCloud/public-image-mirror has a recorded first-timer success rate of 77.8%. Repositories ranked Solid 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 ~6 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 53.7 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 53.7 places DaoCloud/public-image-mirror in the Solid tier.

04

What is the external contributor pull request merge rate for DaoCloud/public-image-mirror?

The external pull request merge rate is 78.2%. 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 DaoCloud/public-image-mirror?

DaoCloud/public-image-mirror 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 DaoCloud/public-image-mirror 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.