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dexterqiu-collab

AI健身教练

作者 dexterqiu-collab · GitHub ↗ · v1.1.0 · MIT-0
linuxdarwinwin32 ⚠ suspicious
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在 OpenClaw 中安装
/install dexter-fitness-coach
功能描述
Personalized fitness planning and workout accountability coach for beginners and intermediates. Use when users want a training plan, workout logging, progres...
使用说明 (SKILL.md)

Dexter Fitness Coach

Provide practical, sustainable fitness coaching for users who want help with training plans, workout accountability, progress tracking, and basic recovery or nutrition guidance.

Use a supportive coach tone. Be clear, concrete, and safe. Optimize for consistency and adherence, not extreme plans.

When To Use

Use this skill when the user wants:

  • a training plan
  • a weekly workout routine
  • a home or gym program
  • help logging completed workouts
  • a progress review
  • adjustments after missed workouts, fatigue, or schedule changes
  • basic fitness guidance for fat loss, muscle gain, or general fitness

Intake

Before giving a structured plan, collect the minimum needed:

  • goal: fat loss, muscle gain, general fitness, or maintenance
  • experience level: beginner, intermediate, advanced
  • training location: home, gym, mixed
  • available equipment
  • days per week
  • target session length
  • injuries, pain, or medical limits if relevant

If the user is already returning for follow-up, reuse the known context instead of asking everything again.

What To Produce

Depending on the request, provide one of these:

  • a starter plan for new users
  • a weekly schedule
  • a single-session workout
  • a progression update
  • a deload or recovery-adjusted week
  • a short progress summary
  • a workout log summary from the user’s latest message

Coaching Rules

  1. Keep advice realistic and sustainable.
  2. Prefer simple exercises and progressive overload.
  3. Scale volume to the user’s recovery and schedule.
  4. Ask follow-up questions only when needed for safety or plan quality.
  5. Do not present medical diagnosis or rehab advice as certainty.
  6. If pain, injury, eating disorder risk, or other health concerns are mentioned, keep advice conservative and recommend a qualified professional when appropriate.
  7. Do not invent tracking history the user did not provide.

Default Structure

When generating a plan, use this structure:

  1. Goal summary
  2. Weekly split
  3. Exercises with sets, reps, and rest
  4. Progression guidance
  5. Recovery notes
  6. Next check-in prompt

Workout Logging

When the user reports a workout:

  • summarize what they completed
  • note any obvious progression or consistency signal
  • give one or two concrete next-step suggestions
  • keep the response short unless they ask for analysis

If the workout details are incomplete, infer only low-risk structure and state that you are making a best-effort summary.

Nutrition Boundaries

You may give general guidance on:

  • protein targets
  • meal consistency
  • hydration
  • calorie awareness

Do not provide aggressive dieting instructions or clinical nutrition advice.

Safety

Avoid:

  • max-effort prescriptions for beginners
  • punishment framing for missed workouts
  • unsafe progression jumps
  • medical claims

Invocation

Install with:

clawhub install dexter-fitness-coach

After installation, start with a plain-language request such as:

I want a 3-day gym plan for fat loss. I am a beginner.

Repository Notes

This package is distributed primarily as a markdown skill. The Python files in this repository are a reference implementation and local prototype, not a verified cross-platform OpenClaw runtime contract.

安全使用建议
This package appears to be a legitimate fitness coach, but the repository contains runnable Python code and configuration that differ from the published 'instruction-only' claim. Before installing: 1) Confirm whether your OpenClaw host will execute the Python entrypoint (openclaw.yaml) or treat the package purely as a markdown skill — if the host runs the Python, the code will create files in your home directory and may call external APIs. 2) Do not provide LLM API keys or Feishu app_id/app_secret unless you trust the publisher; Feishu sync and LLM calls are optional but the repo/config reference them and openclaw.yaml marks an api_key as required. 3) If you install, consider setting feishu.enabled=false and review/override the data_dir in config.yaml to a location you control (or disable persistence) to avoid unexpected local storage. 4) Inspect openclaw.yaml and fitness_coach.py yourself (or ask the maintainer) to confirm which credentials/configs the host will actually request. If you are uncertain, treat this as untrusted code and avoid supplying secrets or allowing the host to run the Python files.
功能分析
Type: OpenClaw Skill Name: dexter-fitness-coach Version: 1.1.0 The skill bundle implements a fitness coaching system that includes high-risk capabilities such as local file system persistence and outbound network communication. Specifically, 'memory_manager.py' performs read/write operations within the user's home directory (~/.claude/skills/fitness-coach/data), and 'feishu_integration.py' makes outbound HTTPS requests to the Feishu (Lark) API (open.feishu.cn) to sync user data. While these behaviors are aligned with the stated purpose of tracking workouts and providing integrations, the presence of file I/O, network access, and shell scripts (openclaw.sh, publish-to-github.sh) meets the threshold for a suspicious classification under the provided criteria for risky capabilities.
能力评估
Purpose & Capability
The code (training_planner, memory_manager, feishu_integration, fitness_coach) implements a fitness coach consistent with the skill description. Requesting local storage and optional Feishu sync is plausible for this purpose. However, openclaw.yaml and config.yaml reference an LLM API key and Feishu credentials which are not declared in the registry metadata (no required env vars). That mismatch is noteworthy but could be explained by the repo providing an optional runtime implementation.
Instruction Scope
SKILL.md emphasizes a markdown-first skill and does not instruct reading or writing arbitrary files, but the included Python code will persist user profiles, conversation memories, and logs to the user's home directory (~/.claude/skills/fitness-coach/data) and can call external APIs. If the host executes the Python entrypoint (openclaw.yaml points to fitness_coach.py), the skill will create files and may transmit data to Feishu/LLM endpoints when configured. SKILL.md's claim that Python files are 'reference' but untrusted by default conflicts with the presence of an executable entry in openclaw.yaml.
Install Mechanism
There is no install spec in the registry (skill is instruction-only), which is low-risk in isolation. But the repo contains shell scripts (openclaw.sh, publish-to-github.sh) and an openclaw.yaml that declares a Python main — if the OpenClaw host honors that file and executes Python code, the code will be written to disk and run. No remote download URLs or third-party installers were found.
Credentials
Registry metadata lists no required environment variables or credentials, yet config.yaml and openclaw.yaml reference a required LLM api_key and optional Feishu app_id/app_secret. The code will skip Feishu calls if credentials are missing, but openclaw.yaml marks api_key as a required config item. This inconsistency could cause a host to prompt for secrets the SKILL.md did not advertise — ask the publisher which credentials are actually required and why.
Persistence & Privilege
The skill does persist user data locally (JSON files under ~/.claude/... by default) and stores recent conversation history. always:false (not force-included) and disable-model-invocation:false are fine. Persistence is functionally reasonable for a memory-enabled coach, but you should be aware that conversation logs and profile data will be written to disk unless you change the data_dir or disable memory.
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 dexter-fitness-coach
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /dexter-fitness-coach 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
v1.1.0
Convert package to canonical SKILL.md skill format and document Python files as reference implementation
v1.0.2
Align OpenClaw install docs and slug with dexter-fitness-coach
v1.0.1
Fix: Add OpenClaw compatibility and improve search visibility
v1.0.0
Initial release: 24/7 AI fitness coach with personalized training plans and progress tracking
元数据
Slug dexter-fitness-coach
版本 1.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 4
常见问题

AI健身教练 是什么?

Personalized fitness planning and workout accountability coach for beginners and intermediates. Use when users want a training plan, workout logging, progres... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 119 次。

如何安装 AI健身教练?

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

AI健身教练 是免费的吗?

是的,AI健身教练 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

AI健身教练 支持哪些平台?

AI健身教练 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux, darwin, win32)。

谁开发了 AI健身教练?

由 dexterqiu-collab(@dexterqiu-collab)开发并维护,当前版本 v1.1.0。

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