mthom/scryer-prolog - Open Source PR Review Scorecard

A modern Prolog implementation written mostly in Rust.

C-Rank Grade: A (Welcoming) - 56/100

External PR Merge Rate: 66%

Response Time: -

First Timer Success: 86%

Frequently Asked Questions

Is mthom/scryer-prolog welcoming to first-time open-source contributors?

mthom/scryer-prolog has a recorded first-timer success rate of 85.7%. 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 mthom/scryer-prolog respond to incoming external pull requests in approximately 0.0 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 56.3 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 56.3 places mthom/scryer-prolog in the A tier.

What is the external contributor pull request merge rate for mthom/scryer-prolog?

The external contributor pull request merge rate for mthom/scryer-prolog is 66.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in mthom/scryer-prolog?

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

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mthom/scryer-prolog

2,460
InactiveA•Welcoming(56/100)Rust

A modern Prolog implementation written mostly in Rust.

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AI Maintainer Review Guidelines

Review Persona

Constructive Code Reviewer

Warmth Score
8.1/10
Patience Score
8.3/10
Nitpick Rate
24%

Balanced & professional review environment in mthom/scryer-prolog. Maintains strict focus on technical quality and test standards.

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
-
No reviewer activity recorded

Average Response Latency

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

Merge Efficiency
66.0%
Moderate PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
85.7%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
13 core
Highly collaborative maintainer core
Diagnostic Health HUD
66.0%
Merge Gauge
85.7%
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 mthom/scryer-prolog
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/mthom/scryer-prolog)](https://getmerged.abhishekco.de/mthom/scryer-prolog?utm_source=github&utm_medium=badge)

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for mthom/scryer-prolog.

View all good first issues directly on GitHub

Looking for more Rust beginner tasks?Explore Rust 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 mthom/scryer-prolog

When evaluating whether to contribute to mthom/scryer-prolog, 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 mthom/scryer-prolog acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 66.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to mthom/scryer-prolog

01

Is mthom/scryer-prolog welcoming to first-time open-source contributors?

mthom/scryer-prolog has a recorded first-timer success rate of 85.7%. 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 ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 56.3 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 56.3 places mthom/scryer-prolog in the Welcoming tier.

04

What is the external contributor pull request merge rate for mthom/scryer-prolog?

The external pull request merge rate is 66.0%. 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 mthom/scryer-prolog?

mthom/scryer-prolog 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 mthom/scryer-prolog 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.