Multi-Agent A-Share Stock Deep Analysis Engine
Paste the following prompt into your AI chat to install this skill:
Install @user_a11b94c4/multi-agent-stock-analyzer by following https://skillhub.cn/install/skillhub.md.
About this skill
Problem
Single A-share judgments often mix conflicting signals: short-term fund flow, earnings trends, technical indicators, and news sentiment are hard to cross-check in one report. Manually assembling data from iwencai, Tencent quotes, and research notes can miss fields or overstate one signal.
How it works
The skill organizes 6 independent agents around a given A-share to debate and cross-validate market, fund-flow, financial, technical, and news signals. Key steps:
- Automatic data-source fallback: prefer
iwencaifor full quotes, fund flow, financial statements, andMACD/KDJ/RSI; withoutIWENCAI_API_KEY, fall back to Tencent Finance API for price, change, volume, turnover,PE/PB, and market cap. - Supplementary data: if
a-stock-datais installed, it adds K-line, research notes, news, and capital-flow context. - Structured output: produces a Markdown report that lists each agent's views, evidence, and disagreements, rather than a single buy/sell signal.
Boundaries
It is intended for automated analysis of public A-share data and requires Python 3.9+. The report is reference material only and not investment advice. A free IWENCAI_API_KEY enables fuller fund-flow and financial coverage; without it, some dimensions are unavailable.
Use Cases
- For a single A-share, combine quotes, fund flow, financials, and technicals into a multi-agent report.
- Without an iwencai API key, perform basic checks on price, valuation, and turnover using Tencent Finance data.
- Turn agent debate output into Markdown for reviewing disagreements and supporting evidence.
- When a-stock-data is available, add K-lines, research notes, news, and capital-flow signals before deciding.
Best For
- Quant analysts studying one A-share: want to cross-check quotes, fund flow, financials, and technicals before forming a view.
- Engineers maintaining stock-data pipelines: need to wire up iwencai, Tencent Finance, and a-stock-data fallback logic.
- Equity research editors: want to convert multi-agent conclusions into a Markdown evidence chain for review.
- Watchlist monitors: need to combine K-lines, research notes, news, and capital-flow signals in one report before judging.
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