Query A-Share Index Valuations with eastmoney-market-valuation

Where this fits

A portfolio analyst asks their agent: "What was the average PE ratio of the CSI 300 over the last week?" Without a dedicated data skill, the agent would scrape financial sites, parse messy HTML, or fail entirely. The eastmoney-market-valuation skill eliminates that friction—it gives any agent a clean, parameterized endpoint to retrieve official daily valuation data for six major A-share indices (Shanghai Composite, CSI 300, Shenzhen Component, ChiNext, STAR 50, Beijing Stock Exchange 50). Whether you're building a research assistant, a market monitor, or an automated reporting pipeline, this skill handles the data retrieval layer so you can focus on analysis.

Why agents benefit

• Precise statistical queries: Agents can answer "What was the total market cap of the ChiNext on 2026-06-08?" without guessing API schemas—just pass market_code=399006 and trade_date.
• Date-range aggregation: Ask "Show daily PE for the SSE Composite from June 1 to June 9" and the agent returns a paginated series, enabling trend analysis or charting.
• Multi-market comparison: Query all indices for a single day by omitting market_code, letting agents compare valuations across markets in one request.
• Context-aware parameter handling: The agent automatically resolves index names to codes (e.g., "沪深300" → 000300) and validates mutually exclusive date parameters, reducing user-input errors.
• Lightweight integration: A single GET endpoint with no authentication or SDK—agents can call it via simple HTTP tools, keeping the skill footprint minimal.

Practical scenarios

Daily market briefing

A morning briefing agent fetches yesterday's valuation for all six indices, extracts PE and closing price, and composes a concise summary for a trading team's Slack channel.

Historical valuation trend

An investment research agent retrieves a 3-month range of CSI 300 PE ratios, computes rolling averages, and highlights valuation anomalies relative to historical percentiles.

Cross-index screening

A quant developer uses the skill to pull same-day data for all indices, then ranks them by price-to-earnings ratio to identify relatively cheap or expensive segments for a rotation strategy.

Add it to your agent workflow

Install the skill using the OpenAgentSkill CLI:

npx skills add FTShare-Lab/FTShare-skill --skill eastmoney-market-valuation

Then instruct your agent to call the endpoint with parameters like:

{
  "market_code": "000300",
  "start_date": "2026-06-01",
  "end_date": "2026-06-09",
  "page_size": 10
}

This returns a paginated list of daily valuation records—ready to be parsed into tables, charts, or narrative insights.

Compare before adopting

Before wiring this skill into production, evaluate it on four dimensions: quality signals—check the GitHub repo (58 stars as of writing) for recent commits, open issues, and test coverage; maintenance freshness—verify the author responds to issues and updates the API mapping when index codes change; alternatives—consider other market data sources (e.g., AkShare, Tushare) to see if their data granularity or latency better fits your use case; workflow fit—confirm the skill's parameter model aligns with how your users naturally phrase queries (e.g., does the agent need to handle Chinese index names? The included mapping helps).

Why it is worth tracking

This skill is part of the growing FTShare ecosystem—a focused, open-source effort to standardize financial data access for agents. Its 58 stars and active repository indicate community interest, and the single-endpoint design makes it easy to audit and swap. If your agent needs reliable A-share valuation data without building a scraper from scratch, this skill is a strong candidate. Revisit it when you scale to more indices or need intra-day data—the current skill covers daily values only. For a full directory of vetted skills, see https://www.openagentskill.com/skills/ftshare-lab-eastmoney-market-valuation —worth checking before you finalize your toolchain.