guqiong96/Lsglang - Open Source PR Review Scorecard

Lsglang is a special extension of sglang that fully utilizes CPU and GPU computing resources with an efficient GPU parallel + NUMA parallel architecture, suitable for MOE model hybrid inference.

C-Rank Grade: D (Risky) - 0/100

External PR Merge Rate: -

Response Time: -

First Timer Success: -

Frequently Asked Questions

What does the Unscored status represent?

This repository currently has no indexed public pull request reviews or activity on GitHub. Some large projects conduct code reviews via external tooling (e.g. Gerrit, Phabricator) or internal monorepos. As soon as public PR review activity is recorded, scores are computed automatically.

Is this project welcoming to external pull requests?

No public review history has been recorded on GitHub for this project yet. Check the project CONTRIBUTING guide or explore active, welcoming alternatives in the same language ecosystem.

What is the external contributor pull request merge rate for guqiong96/Lsglang?

No public pull request merge data is recorded on GitHub for guqiong96/Lsglang. Review workflows may be hosted externally or restricted to core teams.

How fast can I expect code review feedback on my pull request?

Review speed is currently unmeasured due to no public GitHub PR activity. Refer to the repository's contributing guidelines for team workflow norms.

Are there Good First Issues available in guqiong96/Lsglang?

guqiong96/Lsglang does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

guqiong96
guqiong96/LsglangD•Risky111
GitHub
Back to Explorer
guqiong96

guqiong96/Lsglang

111
UnscoredPython

Lsglang is a special extension of sglang that fully utilizes CPU and GPU computing resources with an efficient GPU parallel + NUMA parallel architecture, suitable for MOE model hybrid inference.

Compare•
Jump to:

Run an instant C-Rank check on guqiong96/Lsglang

We score this repo live from GitHub's public pull-request history - usually in under 30 seconds. Results are cached for 24 hours and refreshed when new commits land.

guqiong96/Lsglang is currently Unscored

This repository has no indexed public pull request reviews or activity on GitHub yet. Some large projects conduct code reviews via external tooling or private repositories. As soon as public PR review activity is recorded, C-Rankâ„¢ computes scores automatically.

Explore active & welcoming alternatives
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
CRITICAL BUS FACTOR
Single maintainer
No active GitHub maintainers found (may review internally on Gerrit or internal tools)
Diagnostic Health HUD
0.0%
Merge Gauge
0.0%
1st-Timer
Community Vibe0/100

Embed C-Rank Badge

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

GetMerged C-Rank badge for guqiong96/Lsglang
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/guqiong96/Lsglang)](https://getmerged.abhishekco.de/guqiong96/Lsglang?utm_source=github&utm_medium=badge)

Active Good First Issues (0)

View on GitHub

No cached good first issues currently tracked for guqiong96/Lsglang.

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.

3 ratings required
Maintainer helpfulness
Review speed
Beginner friendliness

Contributor Compatibility & Review Speed Analysis for guqiong96/Lsglang

When evaluating whether to contribute to guqiong96/Lsglang, 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 guqiong96/Lsglang 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 guqiong96/Lsglang

01

Is guqiong96/Lsglang welcoming to first-time open-source contributors?

guqiong96/Lsglang has a recorded first-timer success rate of 0.0%. Repositories ranked Risky 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 0.0 C-Rankâ„¢ score represent?

The C-Rankâ„¢ 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 0.0 places guqiong96/Lsglang in the Risky tier.

04

What is the external contributor pull request merge rate for guqiong96/Lsglang?

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 guqiong96/Lsglang?

guqiong96/Lsglang does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rankâ„¢ Indexing Standard

All metrics displayed for guqiong96/Lsglang 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.