Create personalized triathlon, marathon, and ultra-endurance training plans.

MITAuto-check passedProductivity & Automation

Install Coach

skills CLI
$ npx skills add felixrieseberg/claude-coach --skill coach -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install felixrieseberg/claude-coach coach --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/felixrieseberg/claude-coach.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skill .claude/skills/coach && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
coach
GitHub stars
199
Used in
1 other repo
Token cost
~4.9k tokens
SKILL.md length
1,579 words
Files
8
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Create personalized triathlon, marathon, and ultra-endurance training plans.

  • Works in 12 steps: Check for Existing Strava Data → Ask How They Want to Provide Data → Get Strava API Credentials → …
  • Athletes ask for training plans
  • SKILL.md covers Initial Setup (First-Time Users), Option A: Strava Integration, Option B: Manual Data Entry and Database Access, plus 5 more sections
  • Calls npx; needs CLIENT_SECRET

What it does

Coach is an agent skill from felixrieseberg/claude-coach. Create 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.

Its SKILL.md is about 4.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files (for example `reference/assessment.md`, `reference/load-management.md` and `reference/periodization.md`).

It sits in Productivity & Automation, covering Health and fitness tracking. It works with SQLite. The repository describes itself as: Claude as your endurance coach for marathons, triathlons, Ironman events, and more. The licence is MIT.

When your agent uses it

  • Athletes ask for training plans
  • Workout schedules
  • Race preparation
  • Coaching advice

Example prompts

  • “/coach”

Requirements

  • Node.js
  • A credential in CLIENT_SECRET

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Check for Existing Strava Data
  2. Ask How They Want to Provide Data
  3. Get Strava API Credentials
  4. Generate Authorization URL
  5. Get the Redirect URL
  6. Exchange Code and Sync
  7. Setup
  8. Data Gathering
  9. Athlete Validation
  10. Zone & Load Setup
  11. Plan Design
  12. Plan Delivery

What it can do on your machine

Read from SKILL.md and the folder at commit 20a8107. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • CLIENT_SECRET

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Coach loads about 4.9k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 1,579 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~4.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from felixrieseberg/claude-coach at commit 20a8107, republished under its MIT licence (© felixrieseberg). 1,579 words, ~4,864 tokens.

Download SKILL.mdSave it as .claude/skills/coach/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
coach
description
Create 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.

Claude Coach: Endurance Training Plan Skill

You 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.

Initial Setup (First-Time Users)

Before creating a training plan, you need to understand the athlete's current fitness. There are two ways to gather this information:

Step 1: Check for Existing Strava Data

First, check if the user has already synced their Strava data:

bash
ls ~/.claude-coach/coach.db

If the database exists, skip to "Database Access" to query their training history.

Step 2: Ask How They Want to Provide Data

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"

Option A: Strava Integration

If they choose Strava, first check if database already exists:

bash
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.

Step 1: Get Strava API Credentials

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'"
Step 2: Generate Authorization URL

Run the auth command to generate the OAuth URL:

bash
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:

  1. Open the URL in a browser
  2. Click "Authorize" on Strava
  3. You'll be redirected to a page that won't load (that's expected!)
  4. Copy the entire URL from the browser's address bar and paste it back here
Step 3: Get the Redirect URL

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'"
Step 4: Exchange Code and Sync

Run these commands to complete authentication and sync (the CLI extracts the code from the URL automatically):

bash
npx claude-coach auth --code="FULL_REDIRECT_URL"
npx claude-coach sync --days=730

This will:

  1. Exchange the code for access tokens
  2. Fetch 2 years of activity history
  3. Store everything in ~/.claude-coach/coach.db
SQLite Requirements

The sync command stores data in a SQLite database. The tool automatically uses the best available option:

  1. Node.js 22.5+: Uses the built-in node:sqlite module (no extra installation needed)
  2. Older Node versions: Falls back to the sqlite3 CLI tool
Refreshing Data

To get latest activities before creating a new plan:

bash
npx claude-coach sync

This uses cached tokens and only fetches new activities.


Option B: Manual Data Entry

If they choose manual entry, gather the following through conversation. Ask naturally, not as a rigid form.

Required Information

1. Current Training (last 4-8 weeks)

  • Weekly hours by sport: "How many hours per week do you typically train? Break it down by swim/bike/run."
  • Longest recent sessions: "What's your longest ride and run in the past month?"
  • Consistency: "How many weeks have you been training consistently?"

2. Performance Benchmarks (whatever they know)

  • Bike: FTP in watts, or "how long can you hold X watts?"
  • Run: Threshold pace, or recent race times (5K, 10K, half marathon)
  • Swim: CSS pace per 100m, or recent time trial result
  • Heart rate: Max HR and/or lactate threshold HR if known

3. Training Background

  • Years in the sport
  • Previous races: events completed with approximate times
  • Recent breaks: any time off in the past 6 months?

4. Constraints

  • Injuries or health considerations
  • Schedule limitations (travel, work, family)
  • Equipment: pool access, smart trainer, etc.
Creating a Manual Assessment

When working from manual data, create an assessment object with the same structure as you would from Strava data:

json
{
  "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:

  • Be conservative with volume prescriptions until you understand their true capacity
  • Ask clarifying questions if something seems inconsistent
  • Default to slightly easier if uncertain - it's better to underestimate than overtrain
  • Note in the plan that zones are estimated and should be validated with field tests

Database Access

The athlete's training data is stored in SQLite at ~/.claude-coach/coach.db. Query it using the built-in query command:

bash
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:

  • activities: All workouts (id, name, sport_type, start_date, moving_time, distance, average_heartrate, suffer_score, etc.)
  • athlete: Profile (weight, ftp, max_heartrate)
  • goals: Target events (event_name, event_date, event_type, notes)

Reference Files

Read these files as needed during plan creation:

FileWhen to ReadContents
skill/reference/queries.mdFirst step of assessmentSQL queries for athlete analysis
skill/reference/assessment.mdAfter running queriesHow to interpret data, validate with athlete
skill/reference/zones.mdBefore prescribing workoutsTraining zones, field testing protocols
skill/reference/load-management.mdWhen setting volume targetsTSS, CTL/ATL/TSB, weekly load targets
skill/reference/periodization.mdWhen structuring phasesMacrocycles, recovery, progressive overload
skill/reference/workouts.mdWhen writing weekly plansSport-specific workout library
skill/reference/race-day.mdFinal section of planPacing strategy, nutrition

Workflow Overview

Phase 0: Setup
  1. Ask how athlete wants to provide data (Strava or manual)
  2. If Strava: Check for existing database, gather credentials if needed, run sync
  3. If Manual: Gather fitness information through conversation
Phase 1: Data Gathering

If using Strava:

  1. Read skill/reference/queries.md and run the assessment queries
  2. Read skill/reference/assessment.md to interpret the results

If using manual data:

  1. Ask the questions outlined in "Option B: Manual Data Entry" above
  2. Build the assessment object from their responses
  3. Read skill/reference/assessment.md for context on interpreting fitness levels
Phase 2: Athlete Validation
  1. Present your assessment to the athlete
  2. Ask validation questions (injuries, constraints, goals)
  3. Adjust based on their feedback
Phase 3: Zone & Load Setup
  1. Read skill/reference/zones.md to establish training zones
  2. Read skill/reference/load-management.md for TSS/CTL targets
Phase 4: Plan Design
  1. Read skill/reference/periodization.md for phase structure
  2. Read skill/reference/workouts.md to build weekly sessions
  3. Calculate weeks until event, design phases
Phase 5: Plan Delivery
  1. Read skill/reference/race-day.md for race execution section
  2. Write the plan as JSON, then render to HTML (see output format below)

Plan Output Format

IMPORTANT: Output the training plan as structured JSON, then render to HTML.

Show full SKILL.md (653 more words)Show less
Step 1: Write JSON Plan

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:

IndicatorLikely Preference
US-based events (Ironman Arizona, Boston Marathon)Imperial: miles for bike/run, yards for swim
European/Australian eventsMetric: km for bike/run, meters for swim
Strava activities show distances in milesImperial
Strava activities show distances in kmMetric
Pool workouts in 25yd/50yd poolsYards for swim
Pool workouts in 25m/50m poolsMeters for swim

When in doubt, ask the athlete during validation. Use round distances that make sense in the chosen unit system:

  • Metric: 5km, 10km, 20km, 40km, 80km (not 8.05km)
  • Imperial: 3mi, 6mi, 12mi, 25mi, 50mi (not 4.97mi)
  • Meters: 100m, 200m, 400m, 1000m, 1500m
  • Yards: 100yd, 200yd, 500yd, 1000yd, 1650yd

Week Scheduling: Weeks must start on Monday or Sunday. Work backwards from race day to determine planStartDate.

Here's the structure:

json
{
  "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"
    }
  }
}

Durations must add up: durationMinutes is the length of the whole session, warm-up and cool-down included. It is the number on the calendar card, in the workout detail and in the sidebar's hour totals, so it is what the athlete plans their day around. humanReadable describes that same session, so its parts must add up to durationMinutes: "10 min warm-up, 4x (3 min hard / 2 min easy), 10 min cool-down" is a 40-minute workout, not 30 and not 45. For parts given as a distance (a 1 mile warm-up, 5x1000m, a 2500m swim), count a realistic time at the prescribed pace. When you change a workout's length (scaling a week to its target hours, trimming a taper), change durationMinutes and humanReadable together, and keep the week's targetHours and summary in line with the new total.

Step 2: Render to HTML

After writing the JSON file, render it to an interactive HTML viewer:

bash
npx claude-coach render plan.json --output plan.html

This creates a beautiful, interactive training plan with:

  • Calendar view with color-coded workouts by sport
  • Click workouts to see full details
  • Mark workouts as complete (saved to localStorage)
  • Week summaries with hours by sport
  • Dark mode, mobile responsive
Step 3: Tell the User

After both files are created, tell the user:

  1. The JSON file path (for data)
  2. The HTML file path (for viewing)
  3. Suggest opening the HTML file in a browser

Key Coaching Principles

  1. Consistency over heroics: Regular moderate training beats occasional big efforts
  2. Easy days easy, hard days hard: Don't let quality sessions become junk miles
  3. Respect recovery: Fitness is built during rest, not during workouts
  4. Progress the limiter: Allocate more time to weaknesses while maintaining strengths
  5. Specificity increases over time: Early training is general; late training mimics race demands
  6. Taper adequately: Most athletes under-taper; trust the fitness you've built
  7. Practice nutrition: Long sessions should include race-day fueling practice
  8. Include strength training: 1-2 sessions/week for injury prevention and power (see workouts.md)
  9. Use doubles strategically: AM/PM splits allow more volume without longer sessions (e.g., AM swim + PM run)
  10. Never schedule same sport back-to-back: Avoid swim Mon + swim Tue, or run Thu + run Fri—spread each sport across the week

Critical Reminders

  • Never skip athlete validation - Present your assessment and get confirmation before writing the plan
  • Distinguish foundation from form - An Ironman finisher who took 3 months off is NOT the same as a beginner
  • Zones must be established before prescribing specific workouts
  • Output JSON, then render HTML - Write the plan as .json, then use npx claude-coach render to create the HTML viewer
  • Explain the "why" - Athletes trust and follow plans they understand
  • Be conservative with manual data - When working without Strava, err on the side of caution with volume and intensity
  • Recommend field tests - For manual data athletes, include zone validation workouts in the first 1-2 weeks
  • Durations must add up - The parts of humanReadable add up to durationMinutes, warm-up and cool-down included (count distance-based parts at the prescribed pace); change both together

© felixrieseberg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files in skill of felixrieseberg/claude-coach.

  • SKILL.md
  • reference/assessment.md
  • reference/load-management.md
  • reference/periodization.md
  • reference/queries.md
  • reference/race-day.md
  • reference/workouts.md
  • reference/zones.md

Open the folder on GitHubat commit 20a8107

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in felixrieseberg/claude-coach, which our catalogue first saw on October 7, 2026.

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Works with

Questions about Coach

What does Coach do?

Create personalized triathlon, marathon, and ultra-endurance training plans. Coach is an agent skill from felixrieseberg/claude-coach. Create personalized triathlon, marathon, and ultra-endurance training plans.

When should I use Coach?

Coach fits situations like: athletes ask for training plans; workout schedules; race preparation; coaching advice.

How do I install Coach in Claude Code?

Run `npx skills add felixrieseberg/claude-coach --skill coach -a claude-code`. Or copy the skill folder (skill in felixrieseberg/claude-coach) into .claude/skills/coach in your project. Claude Code loads it when a task matches its description.

How do I install Coach in Codex?

Run `npx skills add felixrieseberg/claude-coach --skill coach -a codex`. Or copy the skill folder (skill in felixrieseberg/claude-coach) into .agents/skills/coach in your project. Codex loads it when a task matches its description.

Can I use Coach in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add felixrieseberg/claude-coach --skill coach -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/coach, .gemini/skills/coach, .github/skills/coach and .opencode/skills/coach in your project.

What does Coach need to run?

Going by SKILL.md and its folder, Coach needs the command-line tools its instructions call (npx) and credentials named CLIENT_SECRET. Our summary lists: Node.js; A credential in CLIENT_SECRET.

Does Coach access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Coach safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Coach use?

Coach is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Coach use?

About 4.9k tokens (SKILL.md is roughly 19k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Coach?

Skills that share tags, products or a category with Coach: Pp Nutrition (mvanhorn/printing-press-library, 2.1k stars), Health Data (glebis/claude-skills, 390 stars), Wahoo Cloud (LeoYeAI/openclaw-master-skills, 2.2k stars) and Kanban (cyanluna-git/cyanluna.skills, 183 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Coach?

felixrieseberg (a GitHub user) maintains it in felixrieseberg/claude-coach, which has 199 GitHub stars. The repository was last updated on October 5, 2026.

Source: felixrieseberg/claude-coach on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.