Review economics
NanmiCoder/MediaCrawler
Read from the 100 most recently merged pull requests ·
Not enough merged pull requests on both sides yet to compare how they land in review.
≥2%
Attributed
a floor
1
Attributed PRs
99
Other PRs
100
Read
Attributed — the latest 1
The rest — the latest 5
#950 fix(weibo): 修复 RFC2822 时间转换丢弃时区偏移导致时间戳晚 8 小时
1 reviews · 4h to merge
#899 Fix: skip notes that fail to fetch instead of crashing
1 reviews · 43.7d to merge
#925 fix(proxy): raise ValueError for unknown IP_PROXY_PROVIDER_NAME instead of crashing with AttributeError
1 reviews · 5.3d to merge
#909 fix: 修复知乎 specified_id 和已有 Chrome CDP 连接问题
1 reviews · 15.9d to merge
#917 fix: 修复快手翻页逻辑
1 reviews · 29h to merge
How this was measured
2% of merged commits carry agent attribution — a floor, not the share; tools that only complete code inline leave no commit trail, so the unattributed side includes AI-assisted work; 2 PRs came off an agent branch with no commit attribution, so the real share runs higher; reads 100 of 140 merged PRs — the rest have not been analyzed yet.
Detected: Claude Code, OpenAI Codex.
“Attributed” means a commit carried an agent’s signature — a co-author trailer, an agent commit identity, or an agent bot account. Tools that only complete code inline leave no such mark, so the other column is “rest”, not “human-written”. Full method and its limits
The badge reads this repo’s current report, so it follows the number.
Tell me when this moves
We re-read NanmiCoder/MediaCrawler weekly and email only when the number changes materially.
Read your own repos
This one is public. For a private repo, run the same read locally through your own GitHub credentials — nothing is installed and nothing is sent to us.
npx @ambera/review-taxWant this continuously on NanmiCoder/MediaCrawler — each pull request paired to the task it came from, and the work graded from its review loop rather than its diff size? Claim this repo in Forge
Browse every repo people have read · Read a different repository