iit-DLSLab/muse - Open Source PR Review Scorecard

A State Estimation Package for Quadruped Robots, that fuses Proprioceptive and Exteroceptive data

C-Rank Grade: C (Moderate) - 35/100

External PR Merge Rate: -

Response Time: -

First Timer Success: -

Frequently Asked Questions

Is iit-DLSLab/muse welcoming to first-time open-source contributors?

iit-DLSLab/muse has a recorded first-timer success rate of 0.0%. 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 iit-DLSLab/muse 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 35.2 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 35.2 places iit-DLSLab/muse in the C tier.

What is the external contributor pull request merge rate for iit-DLSLab/muse?

The external contributor pull request merge rate for iit-DLSLab/muse is 0.0%, based on public PR activity from non-core contributors.

Are there Good First Issues available in iit-DLSLab/muse?

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

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iit-DLSLab/museC•Moderate139
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iit-DLSLab/muse

139
Active (30d)C•Moderate(35/100)Low Sample (<20 PRs)C++

A State Estimation Package for Quadruped Robots, that fuses Proprioceptive and Exteroceptive data

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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%

Active maintainer team in iit-DLSLab/muse welcoming community pull requests and bug fixes.

Top PR Submission Do's

  • •Ensure code complies with repository style conventions
  • •Keep PRs focused 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
-
No reviewer activity recorded

Average Response Latency

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

Merge Efficiency
0.0%
Selective PR acceptance rate

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
0.0%
No first-timer merges recorded in window

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
1 core
Single maintainer review bottleneck
Diagnostic Health HUD
0.0%
Merge Gauge
0.0%
1st-Timer
Community Vibe0/100

Embed C-Rank Badge

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

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for iit-DLSLab/muse.

View all good first issues directly on GitHub

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Contributor Community Vibe Feedback

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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 iit-DLSLab/muse

When evaluating whether to contribute to iit-DLSLab/muse, 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 iit-DLSLab/muse acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 0.0% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to iit-DLSLab/muse

01

Is iit-DLSLab/muse welcoming to first-time open-source contributors?

iit-DLSLab/muse has a recorded first-timer success rate of 0.0%. 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 ~-. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 35.2 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 35.2 places iit-DLSLab/muse in the Moderate tier.

04

What is the external contributor pull request merge rate for iit-DLSLab/muse?

The external pull request merge rate is 0.0%. 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 iit-DLSLab/muse?

iit-DLSLab/muse 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 iit-DLSLab/muse 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.