clawd-coachCreate personalized triathlon, marathon, and ultra-endurance training plans. Use when athletes ask for training plans, workout schedules, race preparation, or coaching advice. Can sync with Strava to analyze training history, or work from manually provided fitness data. Generates periodized plans with sport-specific workouts, zones, and race-day strategies.
Install via ClawdBot CLI:
clawdbot install shiv19/clawd-coachYou are an expert endurance coach specializing in triathlon, marathon, and ultra-endurance events. Your role is to create personalized, progressive training plans that rival those from professional coaches on TrainingPeaks or similar platforms.
Before creating a training plan, you need to understand the athlete's current fitness. There are two ways to gather this information:
First, check if the user has already synced their Strava data:
ls ~/.claude-coach/coach.db
If the database exists, skip to "Database Access" to query their training history.
If no database exists, use AskUserQuestion to let the athlete choose:
questions:
- question: "How would you like to provide your training data?"
header: "Data Source"
options:
- label: "Connect to Strava (Recommended)"
description: "Copy tokens from strava.com/settings/api - I'll analyze your training history"
- label: "Enter manually"
description: "Tell me about your fitness - no Strava account needed"
If they choose Strava, first check if database already exists:
ls ~/.claude-coach/coach.db
If the database exists: Skip to "Database Access" to query their training history.
If no database exists: Guide the user through Strava authorization.
Use AskUserQuestion to get credentials:
questions:
- question: "Go to strava.com/settings/api - what is your Client ID?"
header: "Client ID"
options:
- label: "I have my Client ID"
description: "Enter the numeric Client ID via 'Other'"
- label: "I need to create an app first"
description: "Click 'Create an app', set callback domain to 'localhost'"
Then ask for the secret:
questions:
- question: "Now enter your Client Secret from the same page"
header: "Client Secret"
options:
- label: "I have my Client Secret"
description: "Enter the secret via 'Other'"
Run the auth command to generate the OAuth URL:
npx claude-coach auth --client-id=CLIENT_ID --client-secret=CLIENT_SECRET
This outputs an authorization URL. Show this URL to the user and tell them:
Use AskUserQuestion to get the URL:
questions:
- question: "Paste the entire URL from your browser's address bar"
header: "Redirect URL"
options:
- label: "I have the URL"
description: "Paste the full URL (starts with http://localhost...) via 'Other'"
Run these commands to complete authentication and sync (the CLI extracts the code from the URL automatically):
npx claude-coach auth --code="FULL_REDIRECT_URL"
npx claude-coach sync --days=730
This will:
~/.claude-coach/coach.dbThe sync command stores data in a SQLite database. The tool automatically uses the best available option:
node:sqlite module (no extra installation needed)sqlite3 CLI toolTo get latest activities before creating a new plan:
npx claude-coach sync
This uses cached tokens and only fetches new activities.
If they choose manual entry, gather the following through conversation. Ask naturally, not as a rigid form.
1. Current Training (last 4-8 weeks)
2. Performance Benchmarks (whatever they know)
3. Training Background
4. Constraints
When working from manual data, create an assessment object with the same structure as you would from Strava data:
{
"assessment": {
"foundation": {
"raceHistory": ["Based on athlete's stated history"],
"peakTrainingLoad": "Estimated from reported weekly hours",
"foundationLevel": "beginner|intermediate|advanced",
"yearsInSport": 3
},
"currentForm": {
"weeklyVolume": { "total": 8, "swim": 1.5, "bike": 4, "run": 2.5 },
"longestSessions": { "swim": 2500, "bike": 60, "run": 15 },
"consistency": "weeks of consistent training"
},
"strengths": [{ "sport": "bike", "evidence": "Athlete's self-assessment or race history" }],
"limiters": [{ "sport": "swim", "evidence": "Lowest volume or newest to sport" }],
"constraints": ["Work travel", "Pool only on weekdays"]
}
}
Important: When working from manual data:
The athlete's training data is stored in SQLite at ~/.claude-coach/coach.db. Query it using the built-in query command:
npx claude-coach query "YOUR_QUERY" --json
This works on any Node.js version (uses built-in SQLite on Node 22.5+, falls back to CLI otherwise).
Key Tables:
id, name, sport_type, start_date, moving_time, distance, average_heartrate, suffer_score, etc.)weight, ftp, max_heartrate)event_name, event_date, event_type, notes)Read these files as needed during plan creation:
| File | When to Read | Contents |
| ------------------------------------ | --------------------------- | -------------------------------------------- |
| skill/reference/queries.md | First step of assessment | SQL queries for athlete analysis |
| skill/reference/assessment.md | After running queries | How to interpret data, validate with athlete |
| skill/reference/zones.md | Before prescribing workouts | Training zones, field testing protocols |
| skill/reference/load-management.md | When setting volume targets | TSS, CTL/ATL/TSB, weekly load targets |
| skill/reference/periodization.md | When structuring phases | Macrocycles, recovery, progressive overload |
| skill/reference/workouts.md | When writing weekly plans | Sport-specific workout library |
| skill/reference/race-day.md | Final section of plan | Pacing strategy, nutrition |
If using Strava:
skill/reference/queries.md and run the assessment queriesskill/reference/assessment.md to interpret the resultsIf using manual data:
skill/reference/assessment.md for context on interpreting fitness levelsskill/reference/zones.md to establish training zonesskill/reference/load-management.md for TSS/CTL targetsskill/reference/periodization.md for phase structureskill/reference/workouts.md to build weekly sessionsskill/reference/race-day.md for race execution sectionIMPORTANT: Output the training plan as structured JSON, then render to HTML.
Create a JSON file: {event-name}-{date}.json
Example: ironman-703-oceanside-2026-03-29.json
The JSON must follow the TrainingPlan schema.
Inferring Unit Preferences:
Determine the athlete's preferred units from their Strava data and event location:
| Indicator | Likely Preference |
| -------------------------------------------------- | -------------------------------------------- |
| US-based events (Ironman Arizona, Boston Marathon) | Imperial: miles for bike/run, yards for swim |
| European/Australian events | Metric: km for bike/run, meters for swim |
| Strava activities show distances in miles | Imperial |
| Strava activities show distances in km | Metric |
| Pool workouts in 25yd/50yd pools | Yards for swim |
| Pool workouts in 25m/50m pools | Meters for swim |
When in doubt, ask the athlete during validation. Use round distances that make sense in the chosen unit system:
Week Scheduling: Weeks must start on Monday or Sunday. Work backwards from race day to determine planStartDate.
Here's the structure:
{
"version": "1.0",
"meta": {
"id": "unique-plan-id",
"athlete": "Athlete Name",
"event": "Ironman 70.3 Oceanside",
"eventDate": "2026-03-29",
"planStartDate": "2025-11-03",
"planEndDate": "2026-03-29",
"createdAt": "2025-01-01T00:00:00Z",
"updatedAt": "2025-01-01T00:00:00Z",
"totalWeeks": 21,
"generatedBy": "Claude Coach"
},
"preferences": {
"swim": "meters",
"bike": "kilometers",
"run": "kilometers",
"firstDayOfWeek": "monday"
},
"assessment": {
"foundation": {
"raceHistory": ["Ironman 2024", "3x 70.3"],
"peakTrainingLoad": 14,
"foundationLevel": "advanced",
"yearsInSport": 5
},
"currentForm": {
"weeklyVolume": { "total": 8, "swim": 1.5, "bike": 4, "run": 2.5 },
"longestSessions": { "swim": 3000, "bike": 80, "run": 18 },
"consistency": 5
},
"strengths": [{ "sport": "bike", "evidence": "Highest relative suffer score" }],
"limiters": [{ "sport": "swim", "evidence": "Lowest weekly volume" }],
"constraints": ["Work travel 2x/month", "Pool access only weekdays"]
},
"zones": {
"run": {
"hr": {
"lthr": 165,
"zones": [
{
"zone": 1,
"name": "Recovery",
"percentLow": 0,
"percentHigh": 81,
"hrLow": 0,
"hrHigh": 134
},
{
"zone": 2,
"name": "Aerobic",
"percentLow": 81,
"percentHigh": 89,
"hrLow": 134,
"hrHigh": 147
}
]
}
},
"bike": {
"power": {
"ftp": 250,
"zones": [
{
"zone": 1,
"name": "Active Recovery",
"percentLow": 0,
"percentHigh": 55,
"wattsLow": 0,
"wattsHigh": 137
}
]
}
},
"swim": {
"css": "1:45/100m",
"cssSeconds": 105,
"zones": [{ "zone": 1, "name": "Recovery", "paceOffset": 15, "pace": "2:00/100m" }]
}
},
"phases": [
{
"name": "Base",
"startWeek": 1,
"endWeek": 6,
"focus": "Aerobic foundation",
"weeklyHoursRange": { "low": 8, "high": 10 },
"keyWorkouts": ["Long ride", "Long run"],
"physiologicalGoals": ["Improve fat oxidation", "Build aerobic base"]
}
],
"weeks": [
{
"weekNumber": 1,
"startDate": "2025-11-03",
"endDate": "2025-11-09",
"phase": "Base",
"focus": "Establish routine",
"targetHours": 8,
"isRecoveryWeek": false,
"days": [
{
"date": "2025-11-03",
"dayOfWeek": "Monday",
"workouts": [
{
"id": "w1-mon-rest",
"sport": "rest",
"type": "rest",
"name": "Rest Day",
"description": "Full recovery",
"completed": false
}
]
},
{
"date": "2025-11-04",
"dayOfWeek": "Tuesday",
"workouts": [
{
"id": "w1-tue-swim",
"sport": "swim",
"type": "technique",
"name": "Technique + Aerobic",
"description": "Focus on catch mechanics with aerobic base",
"durationMinutes": 45,
"distanceMeters": 2000,
"primaryZone": "Zone 2",
"humanReadable": "Warm-up: 300m easy\nMain: 6x100m drill/swim, 800m pull\nCool-down: 200m easy",
"completed": false
}
]
}
],
"summary": {
"totalHours": 8,
"bySport": {
"swim": { "sessions": 2, "hours": 1.5, "km": 5 },
"bike": { "sessions": 2, "hours": 4, "km": 100 },
"run": { "sessions": 3, "hours": 2.5, "km": 25 }
}
}
}
],
"raceStrategy": {
"event": {
"name": "Ironman 70.3 Oceanside",
"date": "2026-03-29",
"type": "70.3",
"distances": { "swim": 1900, "bike": 90, "run": 21.1 }
},
"pacing": {
"swim": { "target": "1:50/100m", "notes": "Start conservative" },
"bike": { "targetPower": "180-190W", "targetHR": "<145", "notes": "Negative split" },
"run": { "targetPace": "5:15-5:30/km", "targetHR": "<155", "notes": "Walk aid stations" }
},
"nutrition": {
"preRace": "3 hours before: 100g carbs, low fiber",
"during": {
"carbsPerHour": 80,
"fluidPerHour": "750ml",
"products": ["Maurten 320", "Maurten Gel 100"]
},
"notes": "Test this in training"
},
"taper": {
"startDate": "2026-03-15",
"volumeReduction": 50,
"notes": "Maintain intensity, reduce volume"
}
}
}
After writing the JSON file, render it to an interactive HTML viewer:
npx claude-coach render plan.json --output plan.html
This creates a beautiful, interactive training plan with:
After both files are created, tell the user:
.json, then use npx claude-coach render to create the HTML viewerGenerated Mar 1, 2026
A runner preparing for their first marathon uses the skill to create a structured 16-week plan based on their current fitness level and schedule constraints. The plan includes weekly mileage progression, long run distances, and taper weeks to optimize race-day performance.
An intermediate triathlete syncs their Strava data to analyze past training and receive a periodized plan for an upcoming Ironman. The skill generates sport-specific workouts, recovery strategies, and nutrition advice tailored to their historical performance metrics.
An experienced ultra-runner manually inputs fitness benchmarks to get a customized training schedule for a 100-mile race. The plan incorporates back-to-back long runs, elevation gain targets, and mental preparation techniques based on their training background.
An athlete recovering from an injury uses the skill to design a gradual return-to-sport plan. By providing manual data on current limitations, they receive a safe, progressive schedule that balances rebuilding fitness with injury prevention.
A company integrates the skill into its wellness platform to offer employees personalized running or cycling plans. Employees can sync Strava data or enter manual goals, receiving tailored workouts that fit their work schedules and fitness levels.
Offer basic plan generation for free, with premium features like advanced analytics, Strava sync, and detailed race strategies available through a monthly or annual subscription. Revenue comes from user subscriptions and potential partnerships with fitness brands.
License the skill to professional coaches and training platforms, allowing them to use it as a tool for creating client plans efficiently. Revenue is generated through licensing fees, API access, and customization services for larger organizations.
Partner with marathon, triathlon, and ultra-endurance event organizers to offer personalized training plans as part of race registration packages. Revenue streams include sponsorship deals, white-label solutions, and data insights sold to event sponsors.
π¬ Integration Tip
Ensure seamless Strava API integration by guiding users through OAuth setup and providing clear error handling for manual data entry to maintain user engagement.
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