smart-strategy-stock-picking

Screens stocks via natural language, structured conditions, or DSL queries against QuantDB factor data.

1.5k|337|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/qusong0627/QuantMind --skill smart-strategy-stock-picking-qusong0627
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: smart-strategy-stock-picking
Source: https://github.com/qusong0627/QuantMind/tree/main/skills/smart-strategy-stock-picking
Command: npx skills add https://github.com/qusong0627/QuantMind --skill smart-strategy-stock-picking-qusong0627

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Manually filtering thousands of stocks across valuation, momentum, technical, and capital-flow dimensions is slow and error-prone. This Skill turns natural language or structured conditions into executable DSL queries against the QuantDB factor store, returning a matched stock pool with quantitative metrics in seconds. ## Core Features & Use Cases - Three Query Modes: Parse free-text requests (e.g. "market cap over 50B and ROE above 15%"), structured numeric/trend/composite conditions, or raw DSL like SELECT symbol WHERE pe < 15 via the QuantMind backend API. - Rich Factor Coverage: Screens across 150+ fields from QuantDB tables including valuation (PE/PB/market cap), technical indicators (MA/RSI/KDJ/MACD), L1 factors (momentum, capital flow, concept heat), sentiment, and margin data. - Multi-Market Support: Query A-shares (SH/SZ/BJ), Hong Kong, US, and crypto markets, with summary statistics like match rate and candidate totals. - Use Case: Ask "find low-valuation blue chips with PE under 15, market cap over 50 billion, and ROE above 10%" and receive a filtered stock pool with per-stock metrics, ready for downstream news analysis, model inference scoring, or factor mining. ## Quick Start Ask the assistant to select A-share stocks where PE is below 15 and ROE is above 10 percent using the smart strategy stock picking skill.

Frequently Asked Questions about smart-strategy-stock-picking

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I screen stocks with natural language conditions?▼

Send your text to the /api/v1/strategy/parse-text endpoint to convert it into DSL, then execute it via /api/v1/strategy/query-pool. For example, "market cap over 50B and ROE above 15%, excluding ST stocks" becomes a SELECT symbol WHERE query.

What factors can I use for quantitative stock screening?▼

The skill supports 150+ fields from QuantDB tables: valuation (pe, pb, market_cap), technicals (ma5, rsi_14, macd_dif), returns (return_20d), volatility (vol_std_20), capital flow (main_flow), concept heat, industry, and ST flags.

Which markets does DSL stock selection support?▼

The query-pool endpoint accepts market values CN, HK, US, and CRYPTO. For A-shares you can further restrict by exchange using SH, SZ, or BJ parameters.

Why does my stock screening query return a 422 error?▼

A 422 means the DSL uses a field outside the backend mapping dictionary. Use the documented common factor names or check the field mappings in backend/services/engine/ai_strategy/steps/step1_stock_selection.py.

Why is my stock screening result empty?▼

Empty results usually mean conditions are too strict. Loosen thresholds, remove some AND clauses, and check summary.matchRate and totalCandidates to verify the candidate universe is normal.