AlexsJones/llmfit - Open Source PR Review Scorecard

Hundreds of models & providers. One command to find what runs on your hardware.

C-Rank Grade: A (Welcoming) - 67/100

External PR Merge Rate: 81%

Response Time: 19h

First Timer Success: 81%

Frequently Asked Questions

Is AlexsJones/llmfit welcoming to first-time open-source contributors?

AlexsJones/llmfit has a recorded first-timer success rate of 81.5%. 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 AlexsJones/llmfit respond to incoming external pull requests in approximately 19.1 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 67.4 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 67.4 places AlexsJones/llmfit in the A tier.

What is the external contributor pull request merge rate for AlexsJones/llmfit?

The external contributor pull request merge rate for AlexsJones/llmfit is 80.9%, based on public PR activity from non-core contributors.

Are there Good First Issues available in AlexsJones/llmfit?

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

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AlexsJones/llmfitA•Welcoming37.7k
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AlexsJones

AlexsJones/llmfit

37,747
Active (30d)A•Welcoming(67/100)Rust

Hundreds of models & providers. One command to find what runs on your hardware.

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AI Maintainer Review Guidelines

Review Persona

Constructive Code Reviewer

Warmth Score
7.6/10
Patience Score
7.9/10
Nitpick Rate
30%

Balanced & professional review environment in AlexsJones/llmfit. 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
19 hours
Standard maintainer review cycle

Average Response Latency

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

Merge Efficiency
80.9%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
81.5%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
29 core
Highly collaborative maintainer core
Diagnostic Health HUD
80.9%
Merge Gauge
81.5%
1st-Timer
Community Vibe72/100

Embed C-Rank Badge

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

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

Active Good First Issues (1)

View on GitHub

I'm a lazy person, and math is annoying. To not do math, having a flag that could cleanly calculate the percentage of my detected VRAM and memory I am willing to allocate to llmfit would be amazing. Thank you! (Will mainly be used to create a DIY profile of preferred settings between different machines dynamically) Problem or motivation llmfit currently supports absolute hardware-capacity overrides: llmfit --memory=10.8GiB llmfit --ram=48GiB This works when the desired budget is known in advance, but it is awkward for applications that want to reserve a percentage of the detected hardware rather than hardcode a capacity. For example, an application may want to allow LLM inference to use at most 90% of detected VRAM so some capacity remains available for the OS, display, desktop applications, CUDA overhead, or other workloads. On a 12 GiB GPU this currently requires the caller to: Detect the GPU's total VRAM separately. Calculate 12 × 0.90 = 10.8 GiB. Pass --memory=10.8GiB. The same

📅 Opened Sep 26, 2026💬 4 comments
Quality: 90/100Contribute
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Contributor Compatibility & Review Speed Analysis for AlexsJones/llmfit

When evaluating whether to contribute to AlexsJones/llmfit, 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 AlexsJones/llmfit acknowledge new external contributions in approximately 19 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 80.9% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to AlexsJones/llmfit

01

Is AlexsJones/llmfit welcoming to first-time open-source contributors?

AlexsJones/llmfit has a recorded first-timer success rate of 81.5%. 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 ~19 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 67.4 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 67.4 places AlexsJones/llmfit in the Welcoming tier.

04

What is the external contributor pull request merge rate for AlexsJones/llmfit?

The external pull request merge rate is 80.9%. 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 AlexsJones/llmfit?

AlexsJones/llmfit 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 AlexsJones/llmfit 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.