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strava-training-coachStrava 训练教练

Agent Skill

strava-training-coach 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

17,798

周安装

720

GitHub Stars

1

下载量

5,587
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:strava-training-coach(Strava 训练教练)
来源仓库:https://github.com/hhq0421/strava-training-coach
安装命令:
openclaw skills install strava-training-coach
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install strava-training-coach

简介

strava-training-coach 作为 AI 跑步教练,通过监控训练负荷预防运动损伤。

  • 适合关注训练强度平衡、里程峰值预警和恢复建议的用户使用。
  • 可检测危险训练趋势,提供个性化调整建议以优化训练效果。
  • 安装前需确认权限范围与维护状态,注意是否涉及联网或数据读写操作。
  • 建议结合来源仓库和 README 进一步验证功能细节与使用限制。

SKILL.md

name
strava-training-coach
description
|
Security
No hardcoded secrets, input validation, log redaction, webhook URL validation,
homepage
https://developers.strava.com/docs/reference/
metadata
{"clawdbot":{"emoji":"🏃","tags":["fitness","strava","running","injury-prevention","training","alerts","discord","slack","health","marathon","overtraining","recovery","80-20-rule","heart-rate","coaching","endurance"],"requires":{"env":["STRAVA_CLIENT_ID","STRAVA_CLIENT_SECRET","DISCORD_WEBHOOK_URL or SLACK_WEBHOOK_URL"]}}}

Strava Training Coach

Evidence-based AI training partner that catches injury risk before you feel it.

Why This Matters

Most running injuries follow the same pattern: too much, too soon. Nielsen et al. (2014) found that runners who increase weekly distance by more than 30% have significantly higher injury rates. By the time you feel pain, the damage is weeks old.

This coach watches your Strava data daily and alerts you before problems become injuries — so you stay consistent instead of sidelined.

Built on the 80/20 polarized training model (Seiler, 2010; Stoggl & Sperlich, 2014) — the same approach used by elite endurance coaches to build durable athletes who train smarter, not just harder.

What You Get

  • ACWR Monitoring — Tracks your acute:chronic workload ratio (Gabbett, 2016). ACWR > 1.5 = high injury risk
  • Acute Load Alerts — Weekly mileage up 30%+? You'll know before your knees do
  • 80/20 Intensity Checks — Too many hard days eroding recovery? Get evidence-based recommendations
  • Recovery Nudges — Extended gaps that might affect your training adaptations
  • Weekly Reports — Sunday summaries with 4-week trends, ACWR, and intensity distribution
  • Oura Integration — Optional sleep/readiness scores to inform training decisions

Quick Start

1. Connect Strava

# Set your Strava API credentials (required)
export STRAVA_CLIENT_ID=your_id
export STRAVA_CLIENT_SECRET=your_secret

# Authenticate (opens browser for OAuth)
python3 scripts/auth.py

Tokens are stored in ~/.config/strava-training-coach/strava_tokens.json with 0600 permissions.

2. Set Up Notifications (Required)

Discord:

export DISCORD_WEBHOOK_URL=https://discord.com/api/webhooks/...
export NOTIFICATION_CHANNEL=discord

Slack:

export SLACK_WEBHOOK_URL=https://hooks.slack.com/...
export NOTIFICATION_CHANNEL=slack

⚠️ Security: Webhook URLs must be set via environment variables. No hardcoded URLs allowed.

3. Optional: Enable Oura Integration

export OURA_ENABLED=true

Requires Oura CLI authentication.

4. Run

# Daily training check + alerts
python3 scripts/coach_check.py

# Weekly summary report  
python3 scripts/weekly_report.py

Optional: schedule with cron for hands-off monitoring:

{
  "name": "Training Coach - Daily Check",
  "schedule": {"kind": "every", "everyMs": 86400000},
  "command": "python3 scripts/coach_check.py"
}

Security Features

This skill is designed with security in mind for ClawHub publication:

Credential Handling

  • No hardcoded secrets — All credentials via environment variables
  • Secure token storage — Tokens saved with 0600 permissions
  • XDG compliance — Config stored in ~/.config/strava-training-coach/
  • Token validation — Structure validation before use

Input Validation

  • Date format validation — ISO8601 format checking
  • Numeric range validation — All thresholds bounded
  • Type checking — Safe type conversion with defaults
  • Webhook URL validation — Pattern matching for Discord/Slack

Data Protection

  • Log redaction — Sensitive data masked in logs
  • Secure temp files — Proper permissions on state files
  • No data leakage — Safe error messages
  • Rate limiting — Max 1 alert per hour per type

Network Security

  • HTTPS only — All API calls use TLS
  • Timeout handling — 30-second timeouts on all requests
  • Retry logic — 3 attempts with exponential backoff
  • Certificate validation — Standard SSL verification

Configuration

All thresholds are optional — sensible defaults with validation.

# Training thresholds (validated ranges)
MAX_WEEKLY_MILEAGE_JUMP=30     # 5-100%, default: 30
MAX_HARD_DAY_PERCENTAGE=25     # 5-100%, default: 25
MIN_EASY_RUN_HEART_RATE=145    # 100-200 bpm, default: 145

# Feature flags
OURA_ENABLED=false             # Enable Oura integration
VERBOSE=false                  # Enable debug logging

Example Alerts

Injury Risk

"Weekly mileage up 45% (18 -> 26 mi). ACWR: 1.62. Nielsen et al. (2014) found >30% weekly increases significantly raise injury risk. Your acute:chronic workload ratio is in the high-risk zone (>1.5). Reduce next week's volume by 20-30%."
"60% of runs were moderate/high effort (HR >145). Seiler (2010) found elite athletes keep ~80% of sessions below VT1. Polarized training produces better VO2max gains than moderate-intensity training (Stoggl & Sperlich, 2014)."
"5 days since last activity. Mujika & Padilla (2000) found VO2max begins declining after ~10 days of inactivity. A gentle 20-min walk or easy jog can maintain adaptations."

Achievements

"30-Day Streak! Consistency beats intensity. Holloszy & Coyle (1984) showed mitochondrial density increases with repeated aerobic stimulus."

Weekly Reports (Sunday)

  • Weekly mileage with week-over-week change %
  • Acute:Chronic Workload Ratio (ACWR) with risk zone
  • Intensity distribution (easy/moderate/hard) vs. 80/20 target
  • 4-week trend visualization
  • Evidence-based recommendations for next week

Training Philosophy (Evidence-Based)

  1. Polarized Training — 80% easy, 20% hard (Seiler & Kjerland, 2006; Stoggl & Sperlich, 2014)
  2. ACWR Sweet Spot — Keep acute:chronic workload ratio between 0.8-1.3 (Gabbett, 2016)
  3. Progressive Overload — Gradual increases; >30% weekly spikes raise injury risk (Nielsen et al., 2014)
  4. Consistency > Intensity — Frequency drives mitochondrial and capillary adaptation (Holloszy & Coyle, 1984)
  5. Strength Training — Reduces sports injuries by 68% and overuse injuries by ~50% (Lauersen et al., 2014)

See references/training-principles.md for the full guide with 30+ scientific references.

Files

  • scripts/auth.py — Strava OAuth setup (tokens stored in XDG config dir)
  • scripts/coach_check.py — Daily training analysis and alerts (security-hardened)
  • scripts/weekly_report.py — Sunday summary reports (security-hardened)
  • references/training-principles.md — Evidence-based injury prevention guide

Smart, Not Spammy

Alerts fire only when something matters:

  • Mileage spike detected
  • Intensity pattern concerning
  • Meaningful PR achieved
  • Weekly summary ready

Not every workout. That's what Strava is for.

Rate Limits

  • 1-2 API calls per check
  • Strava allows 100 req/15 min, 1000/day
  • Daily checks use ~30 requests/month

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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按下载量换算3,997

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敏感数据

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安装前确认

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