Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
**Summary: Major update to prioritize athlete context management and token efficiency.** - Added support for post workout interviews (Reflection as Data) - Added detailed instructions for checking and managing Athlete_Context.md before any data gathering. - Introduced a decision tree to use existing context or initiate a token-efficient context-building workflow. - Clarified when and how to update Athlete_Context.md based on interview count or life/training changes. - Reordered workflow to make athlete context check the first step in every process. - Initial setup, validation, and planning workflows now reference the new context-first logic. - All coaching actions are now to be guided primarily by the athlete context document, when present.
What This Skill Does
Creates personalized training plans for triathlon, marathon, and ultra-endurance events. Can sync with Strava to pull training history or work from manually provided fitness data. Plans include periodized phases, sport-specific workouts, training zones, and race-day strategies.
Stores athlete context in a local file so coaching decisions carry forward across sessions without re-gathering data each time.
When to use it
- Building a 20-week Ironman plan from existing Strava history
- Setting heart rate zones before starting a marathon training block
- Reviewing a tempo run with a guided post-workout interview
- Adjusting training load after returning from injury
- Getting a race-day pacing and nutrition strategy for an upcoming race
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Create a 20-week Ironman training plan
- 1Checks for existing Athlete_Context.md to load prior coaching context
- 2Syncs Strava data and runs assessment commands for stats, foundation, training load, and HR zones
- 3Validates the assessment with the athlete and confirms goals, constraints, and current fitness
- 4Reads zone, load-management, and periodization references to structure training phases
- 5Generates YAML plan and renders it to HTML with race-day pacing and nutrition sections
A 20-week periodized Ironman plan with weekly swim, bike, and run sessions, training zones, TSS targets, and a race-day execution guide
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.