simonlin1212/TradingAgents-astock

A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等),7位分析师基于A股规则的辩论决策,基于TradingAgents深度改造,适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear debate, risk assessment。

2,523
Stars
2 months
Age
0
Published reviews
0
Questions

Reliability breakdown

What drives the reliability score

Component scores measured daily from GitHub activity (2026-07-19).

Continuity30% of headline56

Activity on 40 of 69 tracked days in the last 90 and 13 of 30 in the last 30.

Closure30% of headline52

Merged 5 of 21 PRs opened and closed 50 of 58 issues opened over the last 90 tracked days — PR flow carries 55% of this component, issue flow 45%.

Shipping20% of headline100

14 releases in the last 180 days, 14 in the last 90 and 3 in the last 30 — a steady cadence scores highest.

Liveness10% of headline94

Last push 10 days ago — freshness decays as pushes age (roughly halves every 83 days without a push).

Support burden10% of headline93

9 open issues against 2,523 stars — about 4 open issues per 1,000 stars. Lighter backlogs score higher.

Adoption confidence89

Modeled — how confidently teams are adopting this repo. Stargazers

Maintenance quality70

Modeled from PR/issue responsiveness and upkeep signals. Activity pulse

Risk score22

Modeled — lower is better; adoption and continuity risk. Repository

Stays active (30d)77%

Modeled chance the repo stays active over 30 days. Activity pulse

Stays active (90d)70%

Modeled chance the repo stays active over 90 days. Activity pulse

Release rhythm (180d)100

Regularity of releases over the last 180 days. Releases

Maintainer bus risk (90d)47%

Modeled — lower is better; concentration of commits in few maintainers. Contributors graph

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