EastMoney Futures LHB Skill for AI Agents

Where this fits

A developer building a trading-analysis agent needs to answer user queries like "What's the volume leaderboard for polysilicon futures today?" or "Show me the open-interest ranking for DCE soybeans." Without a reliable data source, the agent would either scrape HTML (fragile) or rely on a paid API. This skill wraps the EastMoney futures leaderboard (龙虎榜) endpoint, giving agents a clean, parameterized way to retrieve complete panel data for any supported exchange, variety, contract, and trade date.

Why agents benefit

• Precise query parameters: Agents can specify exchange, variety, contract, and trade date exactly, avoiding ambiguous natural-language parsing.
• Complete panel in one call: Returns the full array of rankings (volume, open interest, long/short positions) without pagination, so agents don't need to loop through pages.
• Multi-exchange coverage: Supports SHFE, DCE, CZCE, CFFEX, INE, and GFE, enabling cross-market analysis in a single workflow.
• Structured JSON response: The data field contains keys like volume_rank and open_interest_rank with rows of rank, member_name, value, and change—easy to parse into tables or summaries.
• CLI-friendly execution: The skill runs via a simple Python command, making it straightforward to integrate into agent tool-calling loops.

Practical scenarios

Daily market briefing

An agent can fetch the volume leaderboard for a specific contract (e.g., ps2609 on DCE) and generate a concise morning report highlighting top members and their position changes.

Position shift detection

By querying the same variety/contract across consecutive trade dates, an agent can identify significant changes in open-interest rankings, flagging potential market moves for the user.

Cross-exchange comparison

An agent can pull leaderboards for the same product listed on multiple exchanges (e.g., gold on SHFE and INE) and compare member activity to spot arbitrage opportunities.

Add it to your agent workflow

Install the skill using the OpenAgentSkill CLI:

npx skills add FTShare-Lab/FTShare-skill --skill eastmoney-futures-strange

Then invoke it in your agent's tool layer. Example execution:

python <RUN_PY> eastmoney-futures-strange --exchange dce --variety 多晶硅 --contract ps2609 --trade_date 20260721

Replace <RUN_PY> with the absolute path to run.py from the skill directory. The response is a unified code/message/data envelope—your agent can directly convert data into a structured table.

Compare before adopting

Before wiring this skill in, compare it against other futures data sources:

• Quality signals: Check if the returned data matches official exchange reports—look for member names, rank changes, and volume values that align with known market activity.
• Maintenance freshness: Review the GitHub repo (stars, recent commits) to ensure the skill stays updated with EastMoney's API changes.
• Alternatives: Consider whether your agent already has access to a paid futures data API; if so, this skill may be redundant.
• Workflow fit: Verify that the required parameters (exchange, variety, contract, trade date) are easily obtainable from user queries or your agent's context.

Why it is worth tracking

This skill has 58 stars and is authored by FTShare-Lab, indicating community interest and some validation. It solves a niche but recurring problem—futures leaderboard retrieval—with a clean, parameterized interface. Track it if you're building agents that need Chinese futures market data without heavy scraping. Re-evaluate when EastMoney changes their API or if the skill's repo goes stale. For a curated view, see the skill listing at OpenAgentSkill.