Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
C-Rank Grade: A (Welcoming) - 66/100
External PR Merge Rate: 63%
Response Time: -
First Timer Success: 50%
agentscope-ai/QwenPaw has a recorded first-timer success rate of 49.6%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in agentscope-ai/QwenPaw 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.
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 66.2 places agentscope-ai/QwenPaw in the A tier.
The external contributor pull request merge rate for agentscope-ai/QwenPaw is 62.5%, based on public PR activity from non-core contributors.
agentscope-ai/QwenPaw currently has 2 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
Balanced & professional review environment in agentscope-ai/QwenPaw. Maintains strict focus on technical quality and test standards.
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/agentscope-ai/QwenPaw?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 03:00 UTC (03:00 UTC in your timezone). Recommended submission window is Tuesday - Thursday from 06:00 to 10:00 UTC (06:00 - 10:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~16 hours (78% approval). Large PRs (>500 lines) take ~115 hours (28% approval). Keep your diff compact for rapid review.
Adding a new model is way too complicated. Too many clicks back and forth: Go to Settings → Models Find the provider card, click "Settings" to fill in API Key → Save Go back to the provider card list, click "Models" Click "Add Model" and fill in Model ID and Model Name Go back to the Chat page to select the model Adding a single model takes 5 steps, 5 button clicks, and 3 different screens. This is way too complicated. Can you simplify this? Users shouldn't have to click around so much.
Summary 加入一个类似codex steer mode的东西，能够在agent执行过程中补充信息以纠正其行为 Component(s) Affected Core / Backend (app, agents, config, providers, utils, local_models) Console (frontend web UI) Channels (DingTalk, Feishu, QQ, Discord, iMessage, etc.) Skills CLI Documentation (website) Tests CI/CD Scripts / Deploy Problem / Motivation 在实际使用中会出现临时补充信息（发现agent执行思路出错了进行纠正）或者撤回发送错误的消息的情况。目前只能等待上一条消息完整处理完之后才进行反应。可以参考codex等的实现来在执行过程中插入补充消息或者中断。 为了在一些没有指令的频道上（如飞书）流畅交互，可能需要引入一个“快速模型”来判断是插入补充消息、中断还是排队等当前消息处理完毕。 Willing to Contribute I am willing to open a PR for this feature (after discussion).
可以通过我的软件发信息给copaw ，copaw 回答后调用我接口 或者我自己去论查 最好。发过去后返回一个key 我用这个key 去查 有没有信息
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When evaluating whether to contribute to agentscope-ai/QwenPaw, 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 agentscope-ai/QwenPaw acknowledge new external contributions in approximately -. Out of all submitted pull requests from non-core authors in the last 180-day window, 62.5% were successfully merged into the primary branch.
agentscope-ai/QwenPaw has a recorded first-timer success rate of 49.6%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~-. 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 66.2 places agentscope-ai/QwenPaw in the Welcoming tier.
The external pull request merge rate is 62.5%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, agentscope-ai/QwenPaw currently has 2 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for agentscope-ai/QwenPaw 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.