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Lofy Fitness

作者 Harreynish Gowtham · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
1192
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1
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在 OpenClaw 中安装
/install lofy-fitness
功能描述
Fitness accountability for the Lofy AI assistant — workout logging from natural language, meal tracking with calorie/protein estimates, PR detection with Epley formula, gym reminders based on weekly targets, and progress reports. Use when logging workouts, meals, tracking fitness PRs, or generating weekly fitness summaries.
使用说明 (SKILL.md)

Fitness Tracker — Workout & Health Accountability

Tracks workouts, meals, PRs, and fitness consistency. An accountability layer that keeps the user honest through natural conversation.

Data File: data/fitness.json

{
  "profile": { "goal": "", "weight_log": [], "start_date": null },
  "workouts": [],
  "meals": [],
  "prs": {},
  "weekly_summary": [],
  "current_week": { "workout_count": 0, "target": 0, "workouts": [] }
}

Workout Entry Format

{
  "date": "2026-02-07",
  "type": "strength",
  "muscle_groups": ["chest", "triceps"],
  "exercises": [
    { "name": "Bench Press", "sets": [{"weight": 185, "reps": 5}] }
  ],
  "duration_min": 60,
  "notes": ""
}

Meal Entry Format

{
  "date": "2026-02-07",
  "meal": "lunch",
  "description": "Chicken bowl with rice",
  "estimated_calories": 650,
  "estimated_protein_g": 45,
  "time": "12:30"
}

Parsing Natural Language

Workouts

  • "bench 185x5 185x4" → Bench Press, 2 sets: 185×5, 185×4
  • "tricep pushdowns 50x12 x3" → 3 sets of 50×12
  • "went for a 5k run, 28 minutes" → cardio, running, 5km, 28min
  • "did legs" (no details) → log muscle group, note "details not provided", still counts

Meals

  • "had chipotle for lunch" → estimate ~650 cal, ~40g protein
  • "protein shake after gym" → estimate ~200 cal, ~30g protein
  • "skipped breakfast" → note it; if 3+ day pattern, gently mention

PR Detection

After parsing workouts, check each exercise against stored PRs:

  • Epley 1RM = weight × (1 + reps/30)
  • If new 1RM exceeds stored PR: update and celebrate
  • Only celebrate PRs, not every workout

Instructions

  1. Always read data/fitness.json before responding about fitness
  2. Update the JSON immediately after any fitness conversation
  3. Keep responses short — log confirmation + one comment
  4. Nudge logic: max 1 gym reminder per day, only if behind weekly target
  5. Track consistency over intensity — showing up matters more
  6. If user mentions injury or pain, suggest rest. Never push through pain
  7. Weekly report: show trends (improving? plateauing? declining?) with data
安全使用建议
This skill appears to do what it claims, but it will read and write a local file named data/fitness.json containing personal health information (workouts, meals, injuries) and offers no details about where that file lives, who can read it, how long data is kept, or whether it's encrypted. Before installing: 1) Confirm where the agent's working directory (and data/fitness.json) will reside and that it's an appropriate, private location. 2) Consider requiring explicit user confirmation before each write or disabling autonomous invocation for this skill. 3) If you accept persistent storage, periodically inspect and back up or delete the file; consider encrypting it or keeping it inside an approved secure storage area. 4) Note that the skill origin/homepage is unknown — prefer skills with a verifiable source. If you want me to suggest a safer SKILL.md variant (e.g., prompt-based confirmation before writes, configurable storage path, retention policy), I can draft one.
功能分析
Type: OpenClaw Skill Name: lofy-fitness Version: 1.0.0 The OpenClaw AgentSkills skill bundle for 'lofy-fitness' appears benign. The `SKILL.md` file outlines a fitness tracking skill that reads from and writes to a local `data/fitness.json` file, which is necessary for its stated purpose of logging workouts, meals, and tracking progress. There are no instructions for the AI agent to perform malicious actions such as data exfiltration, unauthorized command execution, persistence, or prompt injection attempts to bypass user intent or access unrelated sensitive data. All instructions are directly related to the core functionality of a fitness tracker.
能力评估
Purpose & Capability
Name/description (workout logging, meal estimates, PR detection, weekly summaries) aligns with the instructions and the JSON schema in SKILL.md. The skill does not request unrelated credentials, binaries, or installs.
Instruction Scope
SKILL.md mandates: "Always read data/fitness.json before responding" and "Update the JSON immediately after any fitness conversation." That requires filesystem read/write access to a relative path that is not declared in the skill metadata. It will persist sensitive personal health data (workouts, meals, injuries) but includes no guidance on access control, encryption, retention, or user consent. This persistent logging behavior extends the skill's runtime footprint beyond ephemeral conversation context.
Install Mechanism
Instruction-only skill with no install spec and no code files — low installer risk. Nothing is downloaded or executed by an installer.
Credentials
The skill requests no environment variables or credentials, which is proportionate. However, the skill implicitly requires write access to a local file path (data/fitness.json) not declared in metadata; sensitive health information will be stored there with no stated protections.
Persistence & Privilege
Although always:false, the SKILL.md explicitly instructs the agent to persistently write to a data file after any fitness conversation. Combined with the platform's default autonomous invocation, this means the skill can create/update local logs of personal health data without per-interaction confirmation. There is no mention of limiting writes, user approval, or safe storage.
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 lofy-fitness
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /lofy-fitness 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
Initial release
元数据
Slug lofy-fitness
版本 1.0.0
许可证
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Lofy Fitness 是什么?

Fitness accountability for the Lofy AI assistant — workout logging from natural language, meal tracking with calorie/protein estimates, PR detection with Epley formula, gym reminders based on weekly targets, and progress reports. Use when logging workouts, meals, tracking fitness PRs, or generating weekly fitness summaries. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1192 次。

如何安装 Lofy Fitness?

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

Lofy Fitness 是免费的吗?

是的,Lofy Fitness 完全免费(开源免费),可自由下载、安装和使用。

Lofy Fitness 支持哪些平台?

Lofy Fitness 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 Lofy Fitness?

由 Harreynish Gowtham(@harrey401)开发并维护,当前版本 v1.0.0。

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