Fetch Eastmoney US Stock Daily OHLC with This Agent Skill

Where this fits

A user asks your market-analysis agent: "How did AAL close over the past two weeks?" Your agent needs daily OHLC candles from Eastmoney, but the API is paginated and rejects large date ranges. Without help, you'd hand-write range-splitting, dedup, and retry logic. This skill packages that flow into one tool call with window batching handled internally.

Why agents benefit

• Splits any date range into 3-day windows automatically, so your agent never implements its own batching or trips API limits.
• Merged results are deduplicated and sorted by date, so overlapping window boundaries don't corrupt downstream analytics.
• One interface covers both narrow date queries ("last week") and full-history backfills, reducing the number of tool definitions you maintain.
• Returns structured OHLC rows that feed directly into indicators, CSV exports, or chart rendering.
• The --all flag skips pagination entirely, cutting round-trips when the user wants the complete dataset.

Practical scenarios

Backtesting a moving-average crossover

The user wants six months of daily closes for AAPL to test a simple MA crossover. The agent calls the skill with --stock_code AAPL --start_date 2026-01-01 --end_date 2026-06-30 --all, and gets one merged, sorted dataset ready for indicator calculation.

Weekly performance summary

"How did MSFT do last week?" The agent passes a five-day date range, gets a small paginated response, computes the weekly open-to-close change, and answers without pulling unnecessary history.

Volatility research on a new ticker

A research user asks for full historical daily bars for a rarely-tracked ticker. With no date range, the agent uses the default full pull and gets the entire series in structured form — no manual pagination loops.

Add it to your agent workflow

Install the skill:

npx skills add FTShare-Lab/FTShare-skill --skill eastmoney-us-stock-daily-ohlc

Then call it through the bundled runner:

python run.py --skill eastmoney-us-stock-daily-ohlc --stock_code AAL --start_date 2026-06-01 --end_date 2026-06-10 --all

For full parameter details and runtime notes, see the skill's entry on OpenAgentSkill.

Compare before adopting

Before wiring this in, check three things. First, quality signals: the repo shows 58 stars from FTShare-Lab, but verify recent commits — Eastmoney's endpoint schema can shift without notice. Second, alternatives: if your users need real-time or intraday data, this skill won't cover it; weigh it against other OHLC skills or a direct SDK integration. Third, workflow fit: the skill expects python run.py invocation, so confirm your agent runtime can shell out to subprocesses or plan to wrap it.

Why it is worth tracking

Fifty-eight stars isn't huge, but the skill encodes a real integration pain point: Eastmoney's US-stock endpoint is poorly documented and inconsistent across date ranges. Internalizing the 3-day window batching and deduplication logic means it carries hard-won knowledge your agent would otherwise reimplement. If your users rely on Eastmoney data — common in Chinese-language finance workflows — this is worth evaluating early. Track it for endpoint-stability updates and star momentum before committing.