A-Share Review and Analyse

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name: stock-review description: A-share market automated review and analysis system, generating daily market insights with Gemini AI, supporting publishing to Hugo blog and WeChat Official Account version: 1.0.1 metadata: openclaw: homepage: https://github.com/donvink/stock-review requires: anyBins: - python3 - python

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🚀 Stock Review

👉 Live Demo Blog

GitHub: 👉 https://github.com/Donvink/stock-review

Language

Match user's language: Respond in the same language the user uses. If the user writes in Chinese, respond in Chinese. If the user writes in English, respond in English.

Script Directory

Agent Execution: Determine this SKILL.md directory as {baseDir}, then use {baseDir}/scripts/.py. Ensure Python 3.10+ is installed and dependencies are configured.

| Script | Purpose | |------|------| | scripts/fetch_data.py | Fetch A-share market data (indices, stocks, sectors, etc.) | | scripts/analyze.py | Gemini AI analysis of market data | | scripts/post_to_hugo.py | Publish to Hugo blog | | scripts/post_to_wechat.py | Publish to WeChat Official Account | | scripts/main.py | Main execution script, coordinates the entire workflow |

Configuration Preferences

1. Check if config.yaml exists: {baseDir}/stock-review/config.yaml

2. Check if .env file exists and is configured with GEMINI_API_KEY, WECHAT_APP_ID, WECHAT_APP_SECRET: {baseDir}/stock-review/.env

config.yaml supports: Default publishing platforms | Whether to skip AI analysis by default | Default data backtracking days | Default request delay | Default retry count | API key configuration .env supports: API key configuration

Minimum supported keys (case-insensitive, accepts 1/0 or true/false):

| Key | Default | Description | |-----|---------|------| | date | null | Date in YYYYMMDD format | | force_refresh | false | Whether to force refresh already fetched data | | skip_ai_analysis | false | Whether to skip AI analysis | | platforms | ["hugo"] | Default publishing platforms (['hugo']/['wechat']/['hugo', 'wechat']) | | data_dir | null | Directory for data storage | | max_retries | 3 | Default retry count | | request_delay | 0.5 | Default request delay (seconds) | | backtrack_days | 0 | Default data backtracking days | | type | gemini | Model type | | model_name | gemini-2.5-flash | Model name |

Recommended config.yaml example:

# default configuration for stock review skill
review:
  markets:                          # can include "shanghai", "shenzhen", "hongkong"
    - "shanghai"
    - "shenzhen"
    - "hongkong"
  default_period: "daily"           # can be "daily", "weekly", "monthly"
  date: null                        # can be specific date "YYYYMMDD" like "20260101" or null for today
  force_refresh: false              # whether to force refresh data even if cached data is available
  skip_ai_analysis: false           # whether to skip AI analysis and just return raw data
  platforms: ["hugo"]               # platforms to publish the report, e.g. ['hugo', 'wechat'] or ['hugo'] or ['wechat']
paths:
  data_dir: null                    # directory to store fetched data and cache, null means current project directory
parameters:
  max_retries: 3
  request_delay: 0.5
  backtrack_days: 0
  
models:
  type: "gemini"
  model_name: "gemini-2.5-flash"

.env example:

# Gemini API Key
GEMINI_API_KEY="your_gemini_api_key"
WeChat Official Account Configuration
WECHAT_APP_ID="your_wechat_app_id"
WECHAT_APP_SECRET="your_wechat_app_secret"

How to Get a Gemini API Key:

1. Visit the official portal: Go to https://aistudio.google.com/ and log in with your Google account.

2. Create an API Key: Click "Get API key" in the left sidebar, click "Create API key in new project", and copy the generated string (please save it securely—you won't be able to see the full key again after closing the window).

3. Important Notes: Free Tier: Provides free quota but with request frequency limits (RPM/RPD). Data Privacy: Free tier data may be used for model improvement. For commercially sensitive data, consider enabling the paid mode.

How to Get WeChat Official Account Credentials:

1. Visit https://developers.weixin.qq.com/platform/ 2. Navigate: My Business → Official Account → Development Keys 3. Add a development key, copy the AppID and AppSecret 4. Add the IP address of your machine to the whitelist

Environment Check

Before first use, install the dependencies.

pip install -r {baseDir}/requirements.txt

Check items: Python version | Dependencies | API keys | Network connection | Directory permissions

If any check fails, provide fix guidance:

| Check Item | Fix Method | |-------|----------| | Python version | Install Python 3.10+: brew install python@3.10 (macOS) or apt install python3.10 (Linux) | | Dependencies | Run pip install -r {baseDir}/requirements.txt | | Gemini API key | Configure in .env or via environment variables | | WeChat Official Account credentials | Configure in .env or via environment variables | | Network connection | Check network proxy settings | | Directory permissions | Ensure data/ and content/posts/ directories are writable |

Workflow Overview

Copy this checklist and check items as you progress:

Review Analysis Progress:
[ ] Step 0: Load preferences (config.yaml, .env), determine execution parameters
[ ] Step 1: Fetch market data
[ ] Step 2: Run AI analysis (optional)
[ ] Step 3: Generate report
[ ] Step 4: Publish to platforms
[ ] Step 5: Report complete

Step 0: Load Preferences

Check and load config.yaml settings (see Configuration Preferences section above), parse and store default values for subsequent steps.

Step 1: Fetch Market Data

Fetch the following data for the specified date:

| Data Type | Source | File | |----------|------|------| | Index data | stock_zh_index_spot_sina | data/{date}/index_{date}.csv | | Limit-up pool | stock_zt_pool_em | data/{date}/zt_pool_{date}.csv | | Limit-down pool | stock_zt_pool_dtgc_em | data/{date}/dt_pool_{date}.csv | | Failed limit-up pool | stock_zt_pool_zbgc_em | data/{date}/zb_pool_{date}.csv | | Full market data | stock_zh_a_spot_em | data/{date}/A_stock_{date}.csv | | Top 20 by turnover | Calculated | data/{date}/top_amount_stocks_{date}.csv | | Concept sectors | stock_board_concept_name_em | data/{date}/concept_summary_{date}.csv | | Top traders list | stock_lhb_detail_daily_sina | data/{date}/lhb_{date}.csv | | Watchlist | Calculated | data/{date}/watchlist*_{date}.csv |

Retry Mechanism:

Default 3 retries

0.5 second request interval

Automatic fallback to alternative interfaces on failure

Step 2: Run AI Analysis

CRITICAL: Run AI analysis only if:

--skip-ai is not set

GEMINI_API_KEY is configured (via config.yaml or environment variables)

AI Analysis Prompt:

prompt = f"""
Role Setting: You are a seasoned A-share strategy analyst with 20 years of experience...
Task Description: Conduct a multi-dimensional review based on the [daily review data]:
1. 🚩 Market Sentiment Diagnosis
2. 💰 Core Themes and Capital Flow
3. 🪜 Consecutive Limit-up Gradient and Space Game
4. ⚡ Key Stocks with Abnormal Movements Analysis
5. 🧭 Next Trading Day Strategy Recommendations
📊 Daily Review Data:
{market_summary}
"""

Output: data/{date}/ai_analysis_{date}.md

Step 3: Generate Reports

Market Summary Report:

File: data/{date}/market_summary_{date}.md

Format: Markdown

Content: Tabular summary of all data

AI Analysis Report (if run):

File: data/{date}/ai_analysis_{date}.md

Format: Markdown

Content: In-depth analysis generated by Gemini

Step 4: Publish to Platforms

Hugo Blog Publishing:

python3 {baseDir}/scripts/post_to_hugo.py --market-summary  --ai-analysis  --date 

Output: content/posts/stock-analysis-{YYYY-MM-DD}.md

WeChat Official Account Publishing (requires API credentials):

python3 {baseDir}/scripts/post_to_wechat.py --market-summary-file  --ai-analysis-file  --date  --cover-file  --title