AlvaroLaraFF/overtraining-check
.claude/skills/overtraining-check/SKILL.md
Detect overtraining risk via ACWR, monotony and strain. Use when the user asks "am I overtraining", "should I back off", "is my load too high".
testing
Updated Apr 16, 2026
$ install --global
skillsauthnpx skillsauth add AlvaroLaraFF/strava-coach overtraining-checkInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 16, 2026, 5:40 PM219.2s3 files scanned
SKILL.md
- name:
- overtraining-check
- description:
- >
- allowed-tools:
- Bash(python3 *), Read
overtraining-check
Three-metric overtraining screen based on Foster's training load model:
- ACWR (Acute:Chronic Workload Ratio): >1.5 = injury danger zone
- Monotony: >2.0 = repetitive load (recovery lacking)
- Strain: weekly load × monotony — high values predict illness/injury
Pre-flight: read snapshot for flags
python3 .claude/skills/athlete-snapshot/scripts/read_snapshot.py
Extract hr_max_bpm, hr_rest_bpm from the snapshot and pass as --hr-max,
--hr-rest if the script accepts them. If no snapshot exists, use defaults.
Run
python3 .claude/skills/overtraining-check/scripts/overtraining.py
Present
Traffic-light verdict (RED / YELLOW / GREEN) on top, three metric values below, and one concrete recommendation (e.g., "drop next week's load by 30%", or "keep going, current load is sustainable").
Post-run: update snapshot
python3 .claude/skills/athlete-snapshot/scripts/update_snapshot.py --source overtraining-check --acwr <ACWR> --monotony <MONOTONY> --strain <STRAIN>
Replace placeholders with values from script output. Show alerts if any.
On error: auto-recovery chain
| Error contains | Action |
|---|---|
| No token / StravaAuthError | Invoke strava-setup, retry |
| No activities / Sync first | Invoke strava-sync --level summary, retry |
| anything else | Surface |
Chain at most ONCE.
After presenting: persist to memory (MANDATORY)
Save a qualitative observation to memory — opinions, patterns, coaching notes. Never store raw numeric values (those are recomputable from the DB). Only write if the observation is NEW or CHANGED vs existing memory. See CLAUDE.md → Memory protocol.
Related Skills
AlvaroLaraFF/weekly-log
data-ai
VerifiedTrustedCommunity
Show a weekly training log: activities grouped by ISO week and sport, with totals for distance, time and elevation. Use when the user asks "what did I do this week", "weekly summary", "training log".
SKILL.mdUpdated Apr 16, 2026
AlvaroLaraFF/weather-correlation
tools
VerifiedTrustedCommunity
Cross-reference recent runs/rides with historical weather (temperature, humidity, wind) from Open-Meteo to find correlations with performance. Use when the user asks "do I run worse in the heat", "weather impact", "temperature vs pace".
SKILL.mdUpdated Apr 16, 2026
AlvaroLaraFF/tri-discipline-balance
testing
VerifiedTrustedCommunity
Show how the user's training time and volume distribute across run, ride and swim, and flag underweighted disciplines. Use when the user asks "am I balanced", "discipline balance", "which sport am I neglecting".
SKILL.mdUpdated Apr 16, 2026
AlvaroLaraFF/tri-combined-load
data-ai
VerifiedTrustedCommunity
Compute a combined CTL/ATL/TSB across run, ride and swim for triathletes. Use when the user asks "my combined load", "triathlon training load", "total TSS across sports".
SKILL.mdUpdated Apr 16, 2026