AkShare Analysis
v1.1.2Analyze Hong Kong (5-digit) and A-share (6-digit) stocks across six dimensions to generate BUY/HOLD/SELL signals with confidence scores using akshare data.
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byxlong@coxlong
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
medium confidencePurpose & Capability
The scripts (analyze.py, horizons.py, indicators.py, news.py, render_report.py) implement the described six-dimension stock analysis using akshare and pandas; network calls to akshare are expected for this purpose. One small metadata mismatch: SKILL.md's embedded metadata lists a required binary 'uv' while the registry metadata reported 'no required binaries'. The presence of akshare/pandas/mplfinance in script headers is consistent with the declared functionality.
Instruction Scope
Runtime instructions tell the agent to run the included Python scripts which fetch data from akshare (internet), produce analysis, and create report directories/files. The workflow writes report files into absolute paths like /data/stock-reports/<ticker>/..., and render_report.py reads data.json, chart_data.json and optional ai_analysis.md. These file I/O operations are consistent with report generation but mean the skill will read/write the host filesystem and perform outbound network requests.
Install Mechanism
There is no install spec (instruction-only), so nothing will be automatically downloaded at install time. However, the scripts declare dependencies in comments (akshare, pandas, mplfinance, etc.) but do not supply an automated installer; the host must have these Python packages and the 'uv' runner available. That mismatch can cause runtime failures if dependencies are missing.
Credentials
The skill requests no environment variables or credentials and does not require unrelated secrets. Network access to akshare (and any hosts akshare contacts) is necessary for functionality; no other credentials or external endpoints are requested by the code.
Persistence & Privilege
always:false (normal). The skill writes persistent report files under /data/stock-reports and may create index.html and JSON files there. It does not request elevated platform privileges, does not claim to modify other skills, and does not persist agent configuration, but you should be aware it will create files in absolute filesystem locations.
Assessment
This skill appears to do what it says (akshare-based analysis), but before installing or running it consider the following: 1) Dependency and runtime: the scripts need Python packages (akshare, pandas, mplfinance, etc.) and the 'uv' runner referenced in SKILL.md — make sure they are installed in a controlled environment. 2) Network access: the scripts call akshare which fetches data from the internet; run in an environment where outbound network access to data sources is acceptable. 3) Filesystem writes: the workflow creates report directories and files under /data/stock-reports (absolute path) — ensure you are okay with files being written there or edit the scripts/commands to use a different path or sandbox. 4) Minor code issues: news.py.format_json references an undefined variable 'keywords' (will raise a NameError when using --json); you may want to fix or test the script before relying on it. 5) Review and test in a sandbox: because the skill executes bundled Python code and performs network I/O and file writes, test it in an isolated environment (container or VM) and inspect/install required packages yourself. If you need this run on a shared/production host, consider adjusting paths and verifying dependencies first.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.