Token导航 LogoToken导航

Agent Skill · 研究检索

strava-training-coach(Strava 训练教练)

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。

strava-training-coach 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 7,885。

总安装 17,798周安装 720GitHub Stars 1下载 5,587核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.3

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install strava-training-coach;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

strava-training-coach 怎么安装?

在终端执行 openclaw skills install strava-training-coach。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

strava-training-coach 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

strava-training-coach 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

strava-training-coach 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

strava-training-coach 用的人多吗?

公开数据是累计安装 17,798 次,近一周安装 720 次,下载 5,587 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

strava-training-coach 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
strava-training-coach

Strava 训练教练 · 本页

17,7981接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

OpenClaw

71.55%
按下载量换算3,997

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills