apple-health-exercise-readiness
v1.0.0查询苹果健康当日数据，分析身体状况是否适合锻炼，给出四档建议（重度/中度/轻度/建议休息）并附详细说明。使用 Python 处理数据。
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
medium confidencePurpose & Capability
Name/description, SKILL.md, and the Python script align: the skill asks the user for a local Apple Health export ZIP and parses health metrics to produce a readiness score. No unrelated binaries, credentials, or cloud services are requested.
Instruction Scope
Runtime instructions are narrowly scoped: confirm ZIP exists, run the included Python script, read script JSON output and produce the human-facing advice. The SKILL.md explicitly constrains outputs (no medical diagnosis, call out high-risk signals) and requires only local file access. It does not instruct reading unrelated system files or environment variables.
Install Mechanism
No install spec; this is instruction+script only. The script claims to use only Python standard library modules (zipfile, xml.etree.ElementTree, etc.), which is proportional and low-risk compared to network downloads or external package installs.
Credentials
No required environment variables, credentials, or config paths are declared or referenced in the visible code. The skill's needs (a local Apple Health export ZIP) match the declared requirements.
Persistence & Privilege
always is false and the skill is user-invocable. It does not request persistent privileges or modify other skills/systems. Autonomous model invocation is allowed (platform default) but not combined with other red flags.
Assessment
This skill appears coherent and local: it parses an Apple Health export ZIP and computes a readiness score using only Python standard libraries. Before running: 1) Inspect the full analyze.py file yourself (especially the parts after the truncated region provided here) to confirm there are no network calls, shell.exec calls, or code that writes sensitive files or uploads data. 2) Only run it on Apple Health export files you control — these exports contain sensitive health data. 3) Run it in a safe environment (local machine or isolated VM) if you are unsure. 4) Do not upload your export to unknown third parties; the skill is designed for local processing. If you want higher assurance, paste the remaining portion of analyze.py (the truncated tail) for a complete review.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.