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ligo-gao

stock-industry-analyzer

by ligo-gao · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
473
Downloads
0
Stars
2
Active Installs
1
Versions
Install in OpenClaw
/install stock-industry-analyzer
Description
自动收集国内外财经新闻,分析股票行业趋势,热点公司与技术指标,生成综合评分和买卖建议报告。
Usage Guidance
This skill appears to do what it says (collect/aggregate news, analyze, and write reports locally) but exercise caution before running it: - Review and remove or update example scripts (run_analysis.py, run_simple.py, test_debug.py) that contain hardcoded Windows paths (C:\Users\l31408\...) so they don't inadvertently read from or write to unexpected locations. - Inspect the full analyzer.py for the truncated/garbled snippet seen in the provided excerpt (there is an incomplete exception handler) — run tests or linting locally before use. - pip-installing akshare/yfinance will enable network access to fetch market data; only install these if you trust the network usage and the package versions. - The docs mention NewsAPI and ta-lib but those integrations are not clearly implemented—if you expect those features, verify and add required API keys or libraries explicitly. - Run the skill in a sandboxed/isolated environment (virtualenv, container) and back up any important local data; monitor disk usage because config.json retention is set to keep many records indefinitely. If you want, I can highlight the exact lines with hardcoded paths and the truncated code snippet, or produce a minimal sanitized example (no absolute paths) you can run safely.
Capability Analysis
Type: OpenClaw Skill Name: stock-industry-analyzer Version: 1.0.0 The bundle is a functional stock and industry analysis tool that uses legitimate financial data libraries (akshare, pandas) and a local SQLite database. While several scripts (run_analysis.py, run_simple.py, and test_debug.py) contain hardcoded local Windows file paths (e.g., C:\Users\l31408\...), these appear to be unintentional development artifacts left over from the author's environment rather than malicious indicators. The code lacks any evidence of data exfiltration, unauthorized network communication, or prompt injection attempts.
Capability Assessment
Purpose & Capability
Name/description align with the code: modules fetch news, analyze sentiment/industry, compute simple technicals (via akshare), store results in a local SQLite DB, and generate reports. However README/SKILL.md mention supporting NewsAPI and ta-lib/ta while requirements and fetcher implementation do not fully implement those integrations—this is an inconsistency but not necessarily malicious.
Instruction Scope
SKILL.md instructs installing requirements and running main.py/crons which is appropriate. But example helper scripts (run_analysis.py, run_simple.py, test_debug.py) contain hardcoded absolute Windows paths (C:\Users\l31408\...) and write to those locations; these are developer artifacts that could cause accidental reads/writes outside the repo if a user runs those scripts without review. The fetcher largely returns templated URLs and mock data rather than performing authenticated API calls, so network access is limited but akshare/yfinance (optional) will perform external requests when used.
Install Mechanism
No install spec is provided (instruction-only), so nothing is downloaded or executed automatically by the installer. Dependencies are installed via pip -r requirements.txt per SKILL.md, which is normal and expected for Python projects.
Credentials
The skill declares no required environment variables or credentials. The runtime code does not request secrets or external credentials. It does depend on network-capable libraries (akshare, yfinance) which will make outbound requests for market data — this is consistent with the stated purpose.
Persistence & Privilege
Skill is not marked always:true and does not request special platform privileges. It creates and writes to a local data directory (data/news.db and report files) which is expected for a data-collection/reporting tool. Be aware of data retention settings in config.json (many items set to '永久') which may cause indefinite local storage growth if not adjusted.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install stock-industry-analyzer
  3. After installation, invoke the skill by name or use /stock-industry-analyzer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- 首次发布自动化股票行业分析工具 - 支持新闻收集、行业及个股NLP分析、热点识别和技术指标计算 - 自动定时抓取与清洗国内外财经新闻 - 综合评分模型及买卖建议 - 本地SQLite持久化历史数据与报告 - 支持OpenClaw平台集成与自定义配置
Metadata
Slug stock-industry-analyzer
Version 1.0.0
License MIT-0
All-time Installs 3
Active Installs 2
Total Versions 1
Frequently Asked Questions

What is stock-industry-analyzer?

自动收集国内外财经新闻,分析股票行业趋势,热点公司与技术指标,生成综合评分和买卖建议报告。 It is an AI Agent Skill for Claude Code / OpenClaw, with 473 downloads so far.

How do I install stock-industry-analyzer?

Run "/install stock-industry-analyzer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is stock-industry-analyzer free?

Yes, stock-industry-analyzer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does stock-industry-analyzer support?

stock-industry-analyzer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created stock-industry-analyzer?

It is built and maintained by ligo-gao (@ligo-gao); the current version is v1.0.0.

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