数学建模技能 - 面向 CUMCM、MCM/ICM 等数学建模竞赛的三阶段工作流：建模分析、Python/MATLAB 编程与 DOCX 论文生成。包含丰富的算法资源库(优化/预测/评价/图论/机器学习等)、角色指导文档、论文模板和实用工具脚本
C-Rank Grade: D (Risky) - 25/100
External PR Merge Rate: -
Response Time: <1h
First Timer Success: -
XiaoMaColtAI/math-modeling-skill has a recorded first-timer success rate of 0.0%. Repositories ranked D typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in XiaoMaColtAI/math-modeling-skill respond to incoming external pull requests in approximately 0.2 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
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 24.9 places XiaoMaColtAI/math-modeling-skill in the D tier.
The external contributor pull request merge rate for XiaoMaColtAI/math-modeling-skill is 0.0%, based on public PR activity from non-core contributors.
XiaoMaColtAI/math-modeling-skill does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
[](https://getmerged.abhishekco.de/XiaoMaColtAI/math-modeling-skill?utm_source=github&utm_medium=badge)
Enter your branch size and test coverage below to forecast review turnaround and get 1-click git splitting commands.
No cached good first issues currently tracked for XiaoMaColtAI/math-modeling-skill.
Rate what actually matters after opening a pull request here.
Rate your first-hand PR experience (review speed, maintainer responsiveness, and onboarding ease) to help other contributors.
When evaluating whether to contribute to XiaoMaColtAI/math-modeling-skill, 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 XiaoMaColtAI/math-modeling-skill acknowledge new external contributions in approximately <1 hour. 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.
XiaoMaColtAI/math-modeling-skill 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.
The initial maintainer response time averages ~<1 hour. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
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 24.9 places XiaoMaColtAI/math-modeling-skill in the Risky tier.
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.
XiaoMaColtAI/math-modeling-skill does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.
All metrics displayed for XiaoMaColtAI/math-modeling-skill 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.