基于 Spring Boot 3 + Java 17 + Spring AI + MySQL + MongoDB + Redis + SSE/WebSocket，实现 AI 对话、智能体会话、AI 模拟面试、实时语音转写、长文本语音合成等核心功能。架构清晰、文档完整，支持本地运行与 Docker 一键部署，非常适合作为 Spring Boot AI 应用开发、智能体后端设计与简历展示项目。
C-Rank Grade: B (Solid) - 51/100
External PR Merge Rate: 69%
Response Time: 1d
First Timer Success: 50%
lishuangqiang/AI-Meeting has a recorded first-timer success rate of 50.0%. Repositories ranked B typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in lishuangqiang/AI-Meeting respond to incoming external pull requests in approximately 24.8 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 51.1 places lishuangqiang/AI-Meeting in the B tier.
The external contributor pull request merge rate for lishuangqiang/AI-Meeting is 69.2%, based on public PR activity from non-core contributors.
lishuangqiang/AI-Meeting does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.
Growing Java project in lishuangqiang/AI-Meeting welcoming community pull requests and bug fixes.
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/lishuangqiang/AI-Meeting?utm_source=github&utm_medium=badge)
Historical health & responsiveness evolution
External PR acceptance
First PR success rate
50% receive response in
90% receive response in
Maintainer review activity heatmap & prime window prediction
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Detected: UTC
Maintainers are most responsive around 14:00 UTC (14:00 UTC in your timezone). Recommended submission window is Tuesday - Thursday from 14:00 to 18:00 UTC (14:00 - 18:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (87% approval). Large PRs (>500 lines) take ~119 hours (31% approval). Keep your diff compact for rapid review.
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 lishuangqiang/AI-Meeting.
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When evaluating whether to contribute to lishuangqiang/AI-Meeting, 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 lishuangqiang/AI-Meeting acknowledge new external contributions in approximately 1 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 69.2% were successfully merged into the primary branch.
lishuangqiang/AI-Meeting has a recorded first-timer success rate of 50.0%. Repositories ranked Solid typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~1 days+. 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 51.1 places lishuangqiang/AI-Meeting in the Solid tier.
The external pull request merge rate is 69.2%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
lishuangqiang/AI-Meeting 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 lishuangqiang/AI-Meeting 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.