Claude Fitness Coach (Coach Paddy)

A data-driven, multi-sport AI fitness coach for Claude Code. Coach Paddy reads your watch + strength-log data, turns it into actionable coaching (morning readiness, evening recaps, weekly reviews, adaptive plans), records everything in plain-text local files you own, and surfaces it all in a mobile dashboard you can deploy to Vercel.

中文说明见下方

Three data sources

Coach Paddy is built around three feeds, each handling what it does best:

Garmin and Coros are interchangeable for recovery/running data — use whichever watch you wear (or both, for dual-watch comparison). Xunji is the strength layer: the coach reads your logged lifts and writes new sessions back.

Core logic

Everything is a transparent, tweakable formula in fitness-coach.md — no black box.

• Readiness Score (1-10) — base 5, adjusted by sleep, HRV status vs. baseline, Body Battery, RHR trend, and active injury. Drives whether today is a full, reduced, or rest day.
• Race Confidence Score (0-100%) — Injury(40%) + Load(25%) + Fitness(25%) + Recovery(10%). Triggers a plan pivot if it drops too far.
• ACWR — Acute:Chronic Workload Ratio read directly from Garmin (HR + training-effect based, not mileage-estimated). Safe band 0.8–1.3.
• Volume Load — weight × total working reps per lift, tracked over weeks so progress shows even when the weight doesn't change. Main lifts are tracked separately from accessories.

Local-first recording

No proprietary app database. Every report is read from and written back to markdown files in your own Obsidian vault:

Fitness/
├── Coach Memory.md      # Athlete profile, history, baselines, nutrition, injury log
├── Training Plan.md     # Current plan + strength progress + Volume Load history
├── Recovery Log.md      # Daily: sleep / HRV / RHR / Body Battery / readiness
└── Logs/                # Weekly training logs (morning + evening detail)
    └── 2026-W10 (Mar02-Mar08).md

You own the data, it's diff-able in git, and it's portable. Templates are in examples/.

Mobile dashboard (deploy to Vercel)

The dashboard/ folder is a static single-page app that parses those same local files into a phone-friendly dashboard — race countdowns, Volume Load charts, recovery trends, a Hyrox station radar, trail-prep tracker, and more. Deploy it to Vercel and check your training from anywhere.

cd dashboard
npm run sample          # synthetic demo data
npx vercel deploy --prod

Your real data.json is generated locally and git-ignored — the public deploy only ever shows synthetic sample data. See dashboard/README.md.

Setup

1. Install a watch MCP server

Garmin (global):

uvx --python 3.12 --from git+https://github.com/Taxuspt/garmin_mcp garmin-mcp-auth

Garmin (China, garmin.cn):

GARMIN_IS_CN=true uvx --python 3.12 --from git+https://github.com/BorisBW/garmin-mcp-cn garmin-mcp-auth

Coros: add your Coros MCP server to ~/.claude/settings.json the same way.

2. Register the MCP server(s) in ~/.claude/settings.json

{
  "mcpServers": {
    "garmin": {
      "command": "uvx",
      "args": ["--python", "3.12", "--from", "git+https://github.com/Taxuspt/garmin_mcp", "garmin-mcp"]
    }
  }
}

China users: swap the repo for git+https://github.com/BorisBW/garmin-mcp-cn and add "env": {"GARMIN_IS_CN": "true"}.

3. (Optional) Xunji strength logging

Set your Xunji API token as an environment variable — never hard-code it:

export XUNJI_TOKEN="xjllm_xxxxxxxx"

The skill calls the Xunji Open API with Authorization: Bearer $XUNJI_TOKEN. Movement-name mappings are in xunji-movements.md.

4. Install the skill

cp fitness-coach.md ~/.claude/commands/fitness-coach.md

Then edit the Athlete Profile and Memory Files paths in fitness-coach.md to match your sport and vault.

5. Use it

claude
> /fitness-coach morning      # readiness report before training
> /fitness-coach evening      # training recap + injury check after
> /fitness-coach weekly       # volume + ACWR + strength progress review

Commands

Repo structure

claude-fitness-cn/
├── README.md
├── fitness-coach.md        # The skill (copy to ~/.claude/commands/)
├── xunji-movements.md      # Strength movement name reference
├── examples/               # Obsidian memory-file templates
│   ├── coach-memory.md
│   ├── training-plan.md
│   └── recovery-log.md
└── dashboard/              # Vercel-deployable mobile dashboard
    ├── public/index.html
    ├── scripts/build-data.mjs
    └── scripts/make-sample.mjs

中文说明

基于 Claude Code 的数据驱动多项目 AI 健身教练。Coach Paddy 读取你的手表 + 力量训练数据，转化为可执行的教练建议（晨间准备度、训练后复盘、周度回顾、自适应计划），把一切记录在你自己拥有的纯文本本地文件里，并通过可部署到 Vercel 的手机端 dashboard 随时浏览。

三个数据源

佳明和高驰在恢复/跑步数据上可互换，戴哪块用哪块（或双表对比）。训记是力量层：教练读取你记录的训练，并把新的训练写回。

核心逻辑（全部为透明可调的公式，见 fitness-coach.md）

• 准备度评分 (1-10)：基准 5 分，按睡眠、HRV 状态、Body Battery、RHR 趋势、伤病调整 → 决定今天全力/降量/休息
• 比赛信心评分 (0-100%)：伤病(40%) + 负荷(25%) + 竞技状态(25%) + 恢复(10%)，过低触发计划调整
• ACWR：急性:慢性负荷比，直接读 Garmin（基于心率+训练效果，比里程估算准），安全区 0.8–1.3
• Volume Load：每个动作 重量 × 总工作次数，按周追踪，重量没涨也能看到容量进步；大项与辅助分开追踪

本地优先的记录方式

没有私有 app 数据库，所有报告读写自你自己的 Obsidian 笔记库（Coach Memory.md / Training Plan.md / Recovery Log.md / Logs/）。数据你拥有、可 git diff、可迁移。模板见 examples/。

手机端 Dashboard

dashboard/ 是一个静态单页应用，把上述本地文件解析成手机友好的仪表盘（比赛倒计时、Volume Load 图表、恢复趋势、Hyrox 站点雷达、越野备赛追踪等），部署到 Vercel 随时随地查看。真实 data.json 本地生成且被 git 忽略，公开部署只展示合成示例数据。

License

MIT

Credits

• Garmin MCP Server by Taxuspt
• python-garminconnect by cyberjunky
• Built with Claude Code by Anthropic