A-Share Market Data Fetcher and Validator

Problem It Solves

A-share data often comes from overlapping sources: AKShare, commercial APIs, exchange disclosures, and web aggregation. The hard part is not getting numbers; it is deciding whether they are usable for research, review, or backtesting. This skill is intended for tasks that need stock, sector, or period-level data and must account for adjustment basis, trading status, financial reporting period, announcement timing, and cross-source conflicts.

How It Works

It first identifies the data object, time range, frequency, and intended use, then selects a primary source and fallback sources. For routine work, AKShare is usually the free structured layer for historical quotes, trading calendars, financial fields, sector themes, and supplemental announcements. When financial statements or disclosures matter, the skill adds CNINFO or exchange public pages for cross-checks. For Level-2, tick-by-tick, order book, or market depth requests, it explains official authorization, licensing, permissions, and cost boundaries before offering any substitute data.

The workflow branches into structured primary data, market extension data, high-precision real-time data explanations, and reusable research datasets. It checks key fields for consistency: code and market suffix, valid trading dates, open/high/low/close/vol completeness, high-low logic, suspension logic, reporting period basis, and sampled multi-source agreement. The output includes source, fetch time, adjustment basis, units, and known limitations.

Where It Fits Best

It is suitable for research working papers, financial statement analysis, backtesting data preparation, and pre/post-market review. It does not automatically produce stock recommendations. For high-frequency stable fetching, institutional-grade fields, or serious pre-trade risk validation, use commercial data APIs or official authorized data feeds.