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Health Training Frontdoor

作者 Joao Driessen · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install health-training-frontdoor
功能描述
Narrow first-class front door for live Fitbit/training retrieval via stable JSON actions.
使用说明 (SKILL.md)

Health/Training Front Door

Use this when OpenClaw needs live Fitbit/health/training data in a stable, low-ambiguity way.

This is a thin, typed front door over the canonical Fitbit connector tooling.

Why this exists

fitbit_tools.py is the canonical operational backend, but it still requires low-level CLI composition. This front door provides a narrow action contract so agents can call one stable interface instead of assembling raw shell commands every time.

Contract

Run:

  • node skills/health-training-frontdoor/scripts/request.js '{...json...}'

Input JSON:

{
  "action": "latest_recovery"
}

Supported actions:

  • auth_status
  • latest_recovery
  • quality_flags
  • training_status
  • training_window
  • unified_latest

Optional fields:

  • days (integer)
  • ensureFresh (boolean)
  • source (for unified_latest, default best)

Default behavior by action

  • latest_recovery: fetches latest days of hrv_rmssd,resting_hr,sleep_minutes,sleep_score,data_quality; defaults days=3, ensureFresh=true
  • quality_flags: defaults days=7
  • training_status: defaults days=14, ensureFresh=true
  • training_window: defaults days=14, ensureFresh=true
  • unified_latest: defaults days=14, source=best

Notes

  • Output is compact JSON.
  • This surface is read-only.
  • Interpretation/coaching remains outside this skill.

Training Programming Reference

All programming decisions must be grounded in Practical Programming for Strength Training (Rippetoe & Baker, 3rd Ed.).

Always load before giving any programming advice:

  1. reference/practical-programming/INDEX.md — who Joao is, relevant chapters, reading guide
  2. memory/training-continuity.md — current lifts, recent sessions, health signals

For any programming question, read the relevant sections of reference/practical-programming/book.md directly. The book is the authority.

Backend mapping

This front door maps directly to:

  • fitbit-connector/scripts/fitbit_tools.py

Do not use this to bypass auth or write-capable operations.

安全使用建议
This skill is a small wrapper that calls an existing fitbit_tools.py and returns JSON; that is consistent with its stated purpose. Before installing, verify: 1) where fitbit-connector/scripts/fitbit_tools.py lives in your workspace and that it is trusted; 2) what environment variables or local config that python tool requires (the skill does not declare them but will forward process.env to the child process); 3) the contents of reference/practical-programming/INDEX.md and memory/training-continuity.md mentioned in SKILL.md — they may contain sensitive personal data and the SKILL.md explicitly asks the agent to load them before giving programming advice. If you proceed, ensure only expected credentials are present in the agent environment and audit the referenced fitbit connector code to confirm it is read-only and does not leak data to external endpoints.
功能分析
Type: OpenClaw Skill Name: health-training-frontdoor Version: 1.0.0 The skill acts as a structured wrapper for a local Fitbit data connector. The Node.js script (scripts/request.js) safely executes a Python backend using spawnSync with hardcoded paths and validated arguments, minimizing shell injection risks. The instructions in SKILL.md are consistent with the stated purpose of health data retrieval and RAG-based coaching, with no evidence of malicious intent, data exfiltration, or unauthorized access.
能力评估
Purpose & Capability
Name/description match the code: the Node script is a thin wrapper that invokes fitbit-connector/scripts/fitbit_tools.py and returns JSON. That behavior is coherent with a read-only 'front door' for Fitbit/training retrieval. However the skill does not declare any Fitbit-related environment variables or credentials even though the backend connector almost certainly requires them, which is a proportionality/visibility gap.
Instruction Scope
SKILL.md instructs the agent to "Always load" local content including reference/practical-programming/INDEX.md and memory/training-continuity.md before giving programming advice. Loading memory/training-continuity.md could expose sensitive, user-specific training data; this goes beyond the narrow read-only data-retrieval claim and is a scope creep/conflict (the doc also says "Interpretation/coaching remains outside this skill").
Install Mechanism
There is no install spec (instruction-only plus a small JS script). Nothing is downloaded or written to disk by the skill itself.
Credentials
The wrapper passes process.env through to the child python process and does not declare required env vars. That means any credentials present in the agent environment will be available to the invoked fitbit_tools.py; this may be expected but should be explicit (the skill should document which FITBIT_* or connector-specific env vars it needs).
Persistence & Privilege
always:false and no special persistence or config changes. The skill does spawn a child process but does not request forced always-on privileges or attempt to modify other skills or global agent settings.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install health-training-frontdoor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /health-training-frontdoor 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
health-training-frontdoor v1.0.0 - Introduced a typed front door for live Fitbit/health/training data retrieval using stable JSON actions. - Provides a simplified, read-only API over the canonical Fitbit connector, reducing the need for raw CLI command assembly. - Supports stable actions: `auth_status`, `latest_recovery`, `quality_flags`, `training_status`, `training_window`, and `unified_latest` with clear default behaviors and optional fields. - Ensures all programming advice is grounded in "Practical Programming for Strength Training" and references user-specific context before making recommendations. - Guarantees compact JSON outputs and direct mapping to backend tools, without bypassing authentication or allowing data writes.
元数据
Slug health-training-frontdoor
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Health Training Frontdoor 是什么?

Narrow first-class front door for live Fitbit/training retrieval via stable JSON actions. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 111 次。

如何安装 Health Training Frontdoor?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install health-training-frontdoor」即可一键安装,无需额外配置。

Health Training Frontdoor 是免费的吗?

是的,Health Training Frontdoor 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Health Training Frontdoor 支持哪些平台?

Health Training Frontdoor 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Health Training Frontdoor?

由 Joao Driessen(@joaodriessen)开发并维护,当前版本 v1.0.0。

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