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tnt-likely/panwatch

PanWatch — AI stock monitoring for A-shares, HK & US markets, powered by TradingAgents. Portfolio insights, real-time alerts & automated reports.|盯盘侠:覆盖 A股/港股/美股的 AI 盯盘、持仓分析、实时提醒与自动报告。

PythonrisingLive GitHub sample
View JSON View on GitHub

Current momentum

74capped sample

Stars

2.1K

+27 since sync

Commits

8

in period

Active contributors

2

+0%

Issues closed

43

242.6h avg. resolution

Recorded trajectory

Movement you can verify over time.

Loading daily momentum history.

Behind the number

A score you can inspect.

Each signal contributes points to the total. These are capped GitHub samples, not complete activity counts or proof of adoption.

Development activity40.0 / 40 pts

8 commits · 18 opened PRs · 43 closed issues in 7 days

24 + 22 × ln(1 + weekly weighted activity). Activity = commits + 2 × opened PRs + closed issues. Signal bounded to 0–100, then weighted 40%.

Contributor breadth12.9 / 25 pts

2 sampled contributors in 7 days · 0% contributor-growth input

24 + 25 × ln(1 + contributors × √(7 / days)) + 0.15 × growth. Growth uses the 30-day windows; capped samples use a neutral 0 input. Signal bounded to 0–100, then weighted 25%.

Issue resolution6.7 / 20 pts

242.6 hours resolution input

105 − 9 × log₂(1 + hours). Uses sampled closed issues, not first-response time. With no resolved issues, the model uses 168 hours. Signal bounded to 0–100, then weighted 20%.

Release cadence14.3 / 15 pts

2 days cadence input

105 − 5 × cadence days. With fewer than two published releases, the model uses time since the last push as a proxy. Signal bounded to 0–100, then weighted 15%.

Weighted total · rounded once74 / 100

What changed in the recorded sample?

Loading recorded observations…

393 forks

Downstream adoption

73 open issues

Community demand

2 day cadence

Shipping consistency