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tiantianlaolao/dsh-astock-research

China A-share stock research: ticker search, announcements over any date range, financial report cards, valuation profiles and signal-factor explanations (~5,000 stocks since 2011, public read-only data service), plus a link-out tool to an external trading-sandbox product.

Stars ★ 1 Category Tools & Capabilities Listed 2026-08-20 npm dsh-astock-research

Install

Inside DeepSeek Harness, with dsh-market

dsh plugin --profile web add dshmarket

Or from the command line

dsh plugin --profile web add dsh-astock-research

Installing runs third-party code with your own permissions — it can read your files, use your credentials and reach the network. Review the source first, and pin a commit (github:owner/repo#sha) when you can.

README

中文 | English

A-share (China) stock research assistant — a DeepSeek Harness (dsh) plugin.

Research individual China A-share stocks inside dsh: search tickers, read announcements in plain language, digest financial reports, check valuation profiles, and learn what trading signals mean. Works alongside dsh's built-in web search — authoritative database numbers and live news each play their part. Heavy computation (strategy backtests, reverse signal search, historical trading simulation) is handed off to the AIHEY trading sandbox via links.

Tools

Tool What it does
stock_search Search A-share stocks by name or ticker code
stock_profile Stock profile: price moves, volatility, valuation percentile, fundamentals
stock_announcements Company announcements (any historical date range), interpreted in plain language by the model
stock_financials Financial report numbers as a plain-language card
factor_catalog Explanations of trading signal factors
open_aihey_backtest Hands out an AIHEY trading-sandbox link when backtesting / reverse search / simulation is requested

The plugin also registers a stock-research skill with built-in compliance rules (state facts only, no stock recommendations, disclaimers attached), data-source routing (database vs. web search), and guidance rules.

Install

Prerequisites: Node.js ^22.19 or >=24, and a DeepSeek API key (paste it once in the dsh Web UI under Settings → Models).

npm install -g @deepseek-ai/dsh pnpm             # ① one-time: dsh itself + pnpm (needed for plugin installs)
dsh plugin --profile web add dsh-astock-research  # ② one-time: install this plugin from npm
dsh web                                           # ③ daily startup

Once started, open the address printed in the terminal (default http://127.0.0.1:3080). For everyday use only the last command dsh web is needed.

Already have dsh installed? Just run step ② and restart dsh web.

The commands are identical on macOS / Linux; if step ① fails with a permission error, prefix it with sudo.

Things to ask once installed

Show me Kweichow Moutai's recent announcements
Where does 600519's valuation stand right now?
What share-reduction announcements did CATL make in 2023?
How did BYD do in its latest financial report?
What is a "volume breakout" signal? Is it reliable?

Announcement queries accept any historical date range (e.g. "Vanke's announcements around the 2015 crash"). For heavy computation — strategy backtests, reverse signal search, simulated trading — the assistant hands out a link to the AIHEY trading sandbox.

What it looks like

Moutai's announcements from the last 90 days, annotated in plain language, with a disclaimer at the end:

Announcements explained

When explaining trading signals it states its own boundary — signal scanning and historical win rates belong to the trading sandbox:

Signal explanations and boundaries

Data coverage

Roughly 5,000 A-share stocks across Shanghai, Shenzhen and Beijing exchanges, from 2011 to the present. Hong Kong stocks, US stocks and unlisted companies are not covered (searches return empty; the model will clearly label its data source instead of impersonating database data).

Note: the underlying data service and the AIHEY sandbox are Chinese-language products; tool responses are primarily in Chinese.

About AIHEY

This plugin covers stock research (querying data, reading announcements, explaining concepts). The computation-heavy parts — strategy backtests, reverse signal search, historical trading simulation — are handled by the AIHEY trading sandbox, which is exactly what the open_aihey_backtest tool links to:

Disclaimer

Data comes from public sources and is for research reference only. Nothing here constitutes investment advice.

License

MIT

Content from the project README on GitHub ↗