sissbruecker/linkding - Open Source PR Review Scorecard

Self-hosted bookmark manager that is designed be to be minimal, fast, and easy to set up using Docker.

C-Rank Grade: C (Moderate) - 37/100

External PR Merge Rate: 48%

Response Time: 3d

First Timer Success: 33%

Frequently Asked Questions

Is sissbruecker/linkding welcoming to first-time open-source contributors?

sissbruecker/linkding has a recorded first-timer success rate of 33.3%. Repositories ranked C 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 sissbruecker/linkding respond to incoming external pull requests in approximately 79.2 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 36.6 C-Rank™ score (C 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 36.6 places sissbruecker/linkding in the C tier.

What is the external contributor pull request merge rate for sissbruecker/linkding?

The external contributor pull request merge rate for sissbruecker/linkding is 47.5%, based on public PR activity from non-core contributors.

Are there Good First Issues available in sissbruecker/linkding?

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

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sissbruecker/linkdingCModerate11.1k
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sissbruecker/linkding

11,054
CModerate(37/100)Python

Self-hosted bookmark manager that is designed be to be minimal, fast, and easy to set up using Docker.

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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%

Established Python ecosystem in sissbruecker/linkding. Maintains structured code review standards for external contributors.

Top PR Submission Do's

  • Ensure code complies with Python style conventions
  • Keep PRs scoped and well-documented

Top PR Friction Pitfalls (Don'ts)

  • Do not submit unlinked PRs without context
  • Do not break existing automated test suites
Response Velocity
3 days+
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
47.5%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
33.3%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
15 core
Highly collaborative maintainer core
Diagnostic Health HUD
47.5%
Merge Gauge
33.3%
1st-Timer
Community Vibe29/100

Embed C-Rank Badge

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

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

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for sissbruecker/linkding.

View all good first issues directly on GitHub

Looking for more Python beginner tasks?Explore Python 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 sissbruecker/linkding

When evaluating whether to contribute to sissbruecker/linkding, 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 sissbruecker/linkding acknowledge new external contributions in approximately 3 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 47.5% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to sissbruecker/linkding

01

Is sissbruecker/linkding welcoming to first-time open-source contributors?

sissbruecker/linkding has a recorded first-timer success rate of 33.3%. Repositories ranked Moderate 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 ~3 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 36.6 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 36.6 places sissbruecker/linkding in the Moderate tier.

04

What is the external contributor pull request merge rate for sissbruecker/linkding?

The external pull request merge rate is 47.5%. 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 sissbruecker/linkding?

sissbruecker/linkding 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 sissbruecker/linkding 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.