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daymade-sector-research

Researches A-share sectors via top gainers, announcements, and sentiment evidence grading.

1.4k|216|Updated Oct 22, 2025
Search Tags:#market sentiment#a-share#sector research#cninfo#stock announcements#east money#Investment Analysis
One-click install
npx skills add https://github.com/daymade/claude-code-skills --skill daymade-sector-research
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: daymade-sector-research
Source: https://github.com/daymade/claude-code-skills/tree/main/daymade-financial/daymade-sector-research
Command: npx skills add https://github.com/daymade/claude-code-skills --skill daymade-sector-research

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Conducting sector-level investment research on Chinese A-share markets requires stitching together constituent stock lists, real-time quotes, corporate announcements, and market sentiment from fragmented public data sources, while avoiding fabricated or unverified conclusions.

Core Features & Use Cases

  • Top N Gainers Pipeline: Fetches East Money board constituents and Sina real-time snapshots to rank top N stocks by gain, with full-board distribution bucketing into CSV files.
  • Dual-Source Announcement Retrieval: Queries cninfo and East Money announcement APIs with cross-validation, week/month window bucketing, B-share to A-share code mapping, and zero-result widening checks.
  • Evidence-Graded Sentiment Analysis: Classifies market sentiment evidence into L1 (first-hand quotes), L2 (timestamped media), and L3 (unverified leads), with parallel agent orchestration and adversarial fresh-context verification.
  • Use Case: Ask for the top 10 pharmaceutical stocks today, their announcements from the past week and month, and an evidence-based sentiment judgment, delivered as a verified research report with explicit uncertainty annotations.

Quick Start

Ask the assistant to run a sector research workflow on an A-share industry, for example: give me today's top 10 gainers in the pharmaceutical sector, their announcements from the past week and month, and an evidence-based market sentiment assessment.

Frequently Asked Questions about daymade-sector-research

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

FAQPage Schema
How do I get the top gaining stocks in an A-share sector?▼

Run the top_n_pipeline.py script with an East Money board code like BK1216. It fetches board constituents from the push2 API, pulls Sina real-time snapshots, ranks by percentage gain, and writes top N, full-board quotes, and distribution CSVs.

How to query Chinese listed company announcements by date window?▼

Use the ann_query.py script with stock codes and an end date. It queries cninfo hisAnnouncement as the primary source and East Money np-anotice for cross-validation, bucketing results into one-week and one-month windows in a CSV output.

Does this skill support Beijing Stock Exchange and B-share stocks?▼

Yes. Beijing Stock Exchange codes (43/83/87/92 prefixes) are queried through the cninfo gfbj channel since bse.cn interfaces are unreliable. B-share codes (900/200) are automatically mapped to their corresponding A-share codes for announcement retrieval.

Why does announcement search return zero results for a stock?▼

Zero monthly results often indicate a wrong orgId parameter rather than genuinely no announcements. The script widens to a 90-day window and checks a second source; only when both confirm no recent filings does it conclude the stock truly has no announcements.

What are the limitations of the market sentiment judgment?▼

Sentiment conclusions only rest on L1 first-hand quotes and L2 timestamped media; unverified headlines are listed as pending leads only. Shenwan industry index real-time values and sector capital flow data are unavailable from public endpoints and are explicitly marked as not obtained.

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