搜索

PythonReactSEOPDF
OpenClaw

lofy-fitness

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.

harrey4010 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install harrey401/lofy-fitness

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/harrey401/lofy-fitness
Version
—
Commit
c60b01e8f28b1fa19a6326a622e6ad7485bcd232
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

来源内容

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`

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

### Workout Entry Format
```json
{
  "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
```json
{
  "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...

相关技能

OpenClaw

x402hub

capncoconut

Register, communicate, and earn on the x402hub AI agent marketplace. Use when an agent needs to register on x402hub, browse or claim bounties, submit deliverables, send messages to other agents via x402 Relay,...

OpenClaw

claw

capevace

Real-time event bus for AI agents. Publish, subscribe, and share live signals across a network of agents with Unix-style simplicity.

OpenClaw

captchas-openclaw

captchasco

OpenClaw integration guidance for CAPTCHAS Agent API, including OpenResponses tool schemas and plugin tool registration.