Coach

Installation

Claude Code (plugin)

/plugin marketplace add Andamio-Platform/andamio-marketplace
/plugin install coach@andamio

Pi.dev (npm)

pi install npm:@andamio/coach

Other agents (clone)

git clone https://github.com/Andamio-Platform/coach.git
cd coach

Then point your agent at the skills/ directory.

Quick Start

Run the start skill. Coach will welcome you and ask how you'd like to work. Three paths, one destination:

• Beginner - You want to design a personalized learning experience about something new
• Apprentice - You know some of the content and you're ready to build a course
• Teacher - Have learning targets ready, and you're an expert on the subject

Supported Agents

Coach follows the open Agent Skills standard. The skills/ directory works with any compatible agent:

• Claude Code / Claude
• Cursor
• GitHub Copilot / VS Code
• Gemini CLI
• OpenAI Codex
• Goose
• Roo Code
• And many more

Point your agent at the skills/ directory to get started. See your agent's documentation for how it discovers skills.

How It Works

The Compounding Loop

Each course you develop makes the system smarter for the next one:

Step	Skill	What happens
Draft SLTs	draft-slts	Generate learning targets from topic, audience, and goals
Assess	assess-slts	Evaluate quality across 5 dimensions, suggest rewrites
Revise	(you + agent)	Apply feedback, tighten SLT wording
Classify	classify-lesson-types	Interview to assign each SLT a lesson type
Assess Readiness	self-assess-readiness	Rate coaching confidence per SLT, build context shopping list
Gather Context	gather-screenshots / gather-code-examples	Checklists for Product Demo and Developer Documentation inputs
Build Lessons	(you + agent)	Write lessons using gathered context
Compile	compile	Package modules into platform import format
Compound	compound	Extract patterns into knowledge/ — verb effectiveness, quality issues, calibration, heuristics
Next course		Every skill reads knowledge/ before running. The loop tightens.

The course-workflow skill orchestrates this loop, tracking which phase you're in and suggesting the next step.

Skills

Onboarding Skills

Skill	Purpose
start	Welcome and pathway selection
beginner	Conversation-first flow for designing a learning experience
apprentice	Collaborative flow for structuring content into a course
teacher	Fast-track flow for experts with learning targets ready

Course Development Skills

Skill	Loop Step	Purpose
course-workflow	All	Orchestrates the workflow, tracks status, guides next steps
draft-slts	Draft SLTs	Generates SLTs from topic, audience, and learning goals
assess-slts	Assess	Evaluates SLT quality across 5 dimensions with rewrite suggestions
self-assess-readiness	Assess Readiness	Evaluates coaching readiness per SLT
classify-lesson-types	Classify	Interviews user to classify each SLT by lesson type
gather-screenshots	Gather Context	Screenshot capture checklists for Product Demo lessons
gather-code-examples	Gather Context	Code example checklists for Developer Documentation lessons
compound	Compound	Extracts patterns from course artifacts to improve future runs

Key Concepts

Student Learning Targets (SLTs)

"I can..." statements that define specific, measurable learning outcomes. Each module has one SLT. The skills help you draft them well, assess their quality, and evaluate whether an agent can coach a learner through them.

Fist to Five

A confidence rating (0-5) adapted from Marzano's classroom technique. An agent emits a Fist to Five rating against each SLT based on four dimensions: conceptual explanation, code demonstration, learner assessment, and knowledge currency. Level 5 means the skill can produce work, explain it, catch errors, and evaluate submissions.

The Skill Is the Student

In the classroom, teachers ask "can this student do these things?". Coach asks: "given the context, can these agents do these things?"

Lesson Types

1. Product Demo - SLT + screenshots → visual walkthrough
2. Developer Documentation - SLT + code + docs link → technical lesson
3. How To Guide - SLT + optional materials → step-by-step procedure
4. Organization Onboarding - SLT + org context → setup guidance
5. Exploration - SLT + framing questions → big ideas, thought leadership, worldview challenges

Usage Example

Clone coach, open your agent, and run start. Pick "Beginner" and say you want to teach people how to build CLI tools in Go.

Coach interviews you about your audience and goals, then drafts learning targets like:

"I can parse command-line flags using the flag package by writing a CLI that accepts at least two named arguments."

You pick the ones that fit, refine the wording together, and coach classifies each into a lesson type (walkthrough, documentation, hands-on guide). From there, the workflow builds lessons, compiles them, and extracts patterns into knowledge/ so the next course starts smarter.

Your work-in-progress lives in courses-in-progress/, and compiled output goes to compiled/. Both directories are gitignored except for their ABOUT files - your content stays local.

courses-in-progress/
├── ABOUT.md              # Tracked - explains the directory
└── go-cli-tools/         # Gitignored - your course content
    ├── 00-course.md
    ├── 01-slts.md
    └── lessons/

compiled/
├── ABOUT.md              # Tracked - explains the directory
└── go-cli-tools/         # Gitignored - compiled output
    └── 101/

Using Coach Skills in Another Project

You can bring coach's skills into any project.

Option 1: Plugin install (recommended for Claude Code)

Install via the Andamio marketplace — skills are automatically available as coach:start, coach:draft-slts, etc.

/plugin install coach@andamio

Option 2: npm install

npm install -D @andamio/coach

Skills and seed knowledge are available in node_modules/@andamio/coach/skills/. Note: the compounding loop does not persist in node_modules/ — for full compounding, use the plugin or clone method.

Option 3: Git submodule

Add coach as a submodule and symlink the skills:

cd your-project
git submodule add https://github.com/Andamio-Platform/coach.git .coach
ln -s .coach/skills .agents/skills

Your agent discovers the skills automatically. Knowledge and research are available at .coach/knowledge/.

Option 4: Setup script

For course repos that want full symlink integration (skills, knowledge, and research):

cd /path/to/your-course-repo
/path/to/coach/scripts/setup-course-repo.sh /path/to/coach

See docs/setup-course-repo.md for the full guide.

Option 5: Clone alongside

Clone coach next to your project and point your agent to it:

git clone https://github.com/Andamio-Platform/coach.git

Then configure your agent to look for skills in ../coach/skills/. How you do this depends on your agent - check its documentation for custom skill paths.

Knowledge Compounding

Everything the skills learn lives in knowledge/:

knowledge/
├── index.yaml              # Master index, aggregate stats
├── voice-patterns.md       # Prose style guide for lesson writing
├── slt-patterns/           # Verb bank, quality issues, successful rewrites
├── readiness/              # Context leverage rankings, calibration data
├── lesson-types/           # Heuristics and edge cases
├── lesson-writing/         # Style anti-patterns and acceptable patterns
├── compile/                # Import gotchas discovered during platform uploads
└── research/               # SLT research report (Bloom's, Marzano, Stiggins)

Coach ships with seed patterns extracted from real courses — 33 verbs with Bloom's level mappings, 15 proven SLT rewrites, 33 lesson type heuristics, and calibration rules. These are generic and platform-agnostic.

Making It Yours

When you run /compound after building a course, your patterns are added on top of the seed data. Nothing is overwritten — counts increment, new entries append, and the knowledge base grows to reflect your courses.

To start fresh: delete the contents of each YAML file (keep the schema headers) and run /compound on your first course.

See Knowledge Compounding Guide for the full details on how the loop works, what each file stores, and how to curate or reset.

Adapting for Your Platform

Coach was built for Andamio courses, but 12 of 14 skills are platform-agnostic. The SLT framework, readiness assessment, lesson types, and compounding loop work for any course platform.

See How to Adapt for a guide on making coach work with your platform.

The Andamio Worked Example

This toolkit was built to develop courses on Andamio, a contribution-centered learning platform. The knowledge/ directory ships with real patterns extracted from 7+ Andamio courses.

In Andamio, SLTs are content-addressed by blake2b-256 hash and stored on-chain as credentials. The SLT becomes the bridge between learning and verifiable contribution. If that sounds interesting, explore:

• SLTs as an Agentic Interface - how SLTs work as the operational interface for human-agent collaboration
• Fist to Five for Agents - Marzano's technique adapted for AI agents
• Dual-Audience Courses - designing courses that serve multiple skill levels

Andamio-Specific Skills

Skill	Purpose
compile	Packages a completed module into Andamio import format
andamio-cli	Import/export content via Andamio CLI

Prerequisites

• Any Agent Skills-compatible AI coding agent
• macOS or Linux for the multi-repo symlink setup (Windows users can use WSL)

For Claude Code Users

Coach was originally built with Claude Code. For the best experience, add the compound-engineering plugin to your local .claude/settings.json for Context7 documentation lookup during skill execution. See CLAUDE.md for Claude-specific tips.

Roadmap

Phase A: Build Workflow and Lesson Skills

• 14 skills (10 course development + 4 onboarding pathways)
• Knowledge compounding loop
• Multi-repo setup pattern
• Agent Skills open standard compliance
• Lesson type skills (product-demo, developer-documentation, etc.)
• evaluate-assignment skill for learner submissions

Phase B: Package and Distribute (Current)

• Claude Code plugin (.claude-plugin/plugin.json)
• Andamio marketplace for Claude Code
• npm package (@andamio/coach) for Pi.dev and Vercel Skills CLI
• Community marketplace compatibility (SkillsMP, SkillHub)
• Plugin-aware knowledge architecture (${CLAUDE_PLUGIN_DATA} for persistent compounding)

Phase C: Extend

• Readiness dashboard
• Platform integration APIs

License

MIT

Contributing

See CONTRIBUTING.md.