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Build hands-on, code-first tutorials from technical documentation. Extract real API endpoints, actual code examples, and working scenarios. Create interactive tutorials with copy-paste ready code, real request/response payloads, and step-by-step walkthroughs. Keywords - tutorial, API, hands-on, code-first, copy-paste, interactive, real examples, no fluff

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SKILL.md

name documentation-tutorial
description Build hands-on, code-first tutorials from any primary source - technical documentation, codebases, APIs, tools, or other complex material. Extract real examples, working code, and concrete scenarios. Create tutorials using markdown (text-heavy summaries) or React artifacts (complex interactive workflows). Keywords - tutorial, codebase, API, hands-on, code-first, copy-paste, interactive, real examples, primary source

Tutorial Developer from Primary Sources

Transform any primary source into hands-on, practical tutorials that prioritize real, working examples over conceptual explanations. Focus on what users need to do, not what they need to understand.

Quick Decision Guide

Step 1: Choose format

  • Text-heavy summary or CLI reference → Markdown
  • Complex workflow with multiple steps → React Artifact

Step 2: Follow the three pillars

  1. Real code/commands (not pseudocode)
  2. Real use cases (concrete scenarios)
  3. Mental model (one-sentence explanation)

Core Principles

The Three Pillars

Every tutorial must clearly answer:

  1. Real Code: What's the actual code or command I run? (Copy-paste executable, no pseudocode)
  2. Real Use Cases: When would I actually use this? (Concrete scenarios like "healthcare bot", not vague descriptions)
  3. Mental Model: How does this work? (One-sentence explanation enabling independent problem-solving)

Example:

Mental Model: "AI generates interactive React components from natural language prompts, streaming in real-time."

Code:
curl -X POST https://api.thesys.dev/v1/ui/generate \
  -H "Authorization: Bearer sk-thesys-key" \
  -d '{"prompt": "Create a booking form", "model": "gpt-4"}'

Use Case: When you want users to book appointments without writing React,
send a prompt and stream the form directly into the page.

Code-First Approach

  • Lead with working examples, not theory
  • Real endpoints (actual URLs, not <placeholder>)
  • Exact payloads (complete JSON, not simplified)
  • No high-level summaries unless essential
  • Get users to running code within 5 minutes

Systematic Workflow

Phase 1: Extract from Primary Source

Step 1: Identify Core Mental Model

Answer: "What's the one-sentence explanation that makes everything click?"

Examples:

  • API: "AI generates interactive UIs from prompts, streaming real-time"
  • Tool: "PDFs are structured data; extract tables/text like CSV/JSON"
  • Codebase: "Request flows through middleware → router → handler → response"

Step 2: Find Real Examples

Extract from docs/code:

  • Working code (not pseudocode)
  • CLI commands with actual flags
  • API calls (curl + request/response)
  • Config files, error cases

Step 3: Extract Concrete Use Cases

Wrong: "Can be used for various applications like analytics, reporting, etc."

Right:

  1. Analytics Dashboard: User asks "show me sales by region" → AI generates chart
  2. Booking Flow: Customer books appointment → form auto-generates with calendar
  3. Support Tickets: Agent asks "show ticket queue" → interactive table generates

For each: What triggers it, what code is needed, what user sees, why it matters.

Phase 2: Structure Tutorial

Step 4: Plan Sections (Action-oriented names)

  • Section 1: "⚙️ Setup & Install" → Running in 5 minutes
  • Section 2: "🚀 First API Call" → Verify it works
  • Section 3: "🌐 Core Operations" → Major endpoints
  • Section 4: "🐍 SDK Examples" → Language-specific code
  • Section 5: "💾 Real Scenario" → Complete workflow

Step 5: Plan Code Blocks

  • Copy-paste executable curl with real endpoint
  • Tabs: cURL → Request Body → Response
  • Real data values (names, dates, actual fields)
  • Error cases if documented

Step 6: Plan Workflow

  • Choose actual use case from documentation
  • Break into 3-5 sequential API calls
  • Show how responses flow into next step

Phase 3: Implement

Step 7: For React Artifacts

Structure:

  • Sidebar navigation (6-8 focused sections)
  • Main content area with code blocks
  • Copy buttons on all code
  • Tabbed views (curl/request/response)

Step 8: Code Block Spec

  • Dark background, language label, copy button
  • Left-aligned monospace, syntax highlighting
  • No line numbers (confuses copy-paste)

Step 9: Quality Check (see checklist at end)

Tutorial Patterns

Pattern: API Endpoints

TITLE: Endpoint Name (POST /v1/endpoint)
DESCRIPTION: One sentence
CODE BLOCK: Tabs (cURL | Request | Response)
USE CASE: One sentence + real scenario

Pattern: Complete Workflows

STEP 1: First API Call
  Context (1 sentence) → Code → Result
STEP 2: Second API Call
  Context (how previous flows here) → Code → Result
STEP 3: Final Outcome

Pattern: Setup/Installation

PREREQUISITES: What they need
COMMAND: Full copy-paste command
VERIFY: One-line check
TROUBLESHOOTING: Common issues

Pattern: SDK Examples

LANGUAGE: Python/JavaScript/etc
CODE: Full working function (imports, async/await, error handling)
RUN IT: How to execute
OUTPUT: Expected result

Pattern: Sidebar Navigation

  • 6-8 focused sections (not monolithic)
  • Emoji + action verbs: "⚙️ Setup", "🚀 First Call"
  • Reduces cognitive load, improves completion

Pattern: Copy Buttons

  • One-click copy-to-clipboard (right corner)
  • Visual feedback when copied (checkmark, 2 seconds)
  • 3x higher code execution rate

Pattern: Mental Models First

  • Present one-sentence model after first working example
  • Place in colored box: "💡 How This Works"
  • Enables independent problem-solving

Pattern: Progressive Disclosure

  • Section 1: Minimum to get running
  • Section 2: Simplest successful request
  • Section 3-4: Core operations, multiple languages
  • Section 5: Complete multi-step workflow
  • Section 6: Advanced features
  • Section 7: Troubleshooting

Pattern: Concrete Use Cases

## Common Use Cases

1. **Analytics Dashboard** (5 min read)
   You want users to ask "show me Q3 revenue"
   → AI generates interactive chart

2. **Booking Form** (7 min read)
   You need booking flow without React
   → AI generates form with calendar

[Pick your use case →]

Benefit: Users self-select relevant tutorial path.

Pattern: Troubleshooting

  • Color-coded sections (red=critical, yellow=common)
  • For each: Problem → Root cause → Solution → Code
  • Include CORS, auth failures, timeouts

Quality Checklist

Three Pillars:

  • Real code (copy-paste executable: curl, Python, JavaScript)
  • Real use cases (3-5 concrete scenarios, not "theoretical")
  • Mental model (one-sentence explanation)

Code Quality:

  • Real endpoints (no <placeholder>)
  • Real data (Sarah Chen, 2025-11-15, actual field names)
  • Tabs: cURL + Request + Response
  • Left-aligned, properly formatted

Structure:

  • First section: Running code in <5 minutes
  • 6-8 focused sections with navigation
  • Complete workflow (form → submit → confirm)
  • Multiple languages (Python, JavaScript, HTTP)

Content:

  • Mental model within first 2 examples
  • No conceptual fluff or "learning objectives"
  • Real-world scenario shows data flowing
  • Troubleshooting with real problems

Interactive (for React artifacts):

  • Copy buttons on all code
  • Users can complete real task after tutorial

Real Examples

Example 1: Mail Command (Markdown)

Why Markdown: CLI reference with many commands

Structure: Basic Sending → Advanced Options → Interactive Mode → Reading Mail → Configuration → Gmail Integration → Quick Reference

Key Features: Copy-paste commands, real config files, organized by workflow

Example 2: Thesys C1 API (React Artifact)

Why React: Complex API needing interactive tabs/navigation

Structure: Setup (5min) → First Call → Core Operations → SDK Examples → Real Scenario → Advanced → Troubleshooting

Key Features: Sidebar navigation, copy buttons, tabbed views, real data, workflow chaining

Academic Study Guides: Quote Integration

Same principle applies to academic primary sources (historical documents, philosophical texts, legal cases): transform into practical guide.

Core Principle

Embed quotes throughout analysis where they support arguments. NOT collected at end.

Pattern

Question → Quote → Interpretation → Quote → Synthesis

NOT: Question → Summary → All Quotes at End

Example

## Was Qianlong's Response Wise?

Qianlong defended sovereignty. He explained:

> "If other nations imitate your evil example... how could I possibly comply?"

His reasoning was sound: granting Britain privileges would force him to grant all nations the same.

However, his rejection showed complacency:

> "Strange and costly objects do not interest me."

By dismissing British technology, he missed intelligence-gathering opportunities.

Debate Format

  1. Clear position
  2. 8-10 numbered arguments (each with quote evidence)
  3. Rebuttals section
  4. Conclusion

Each argument: Claim → Quote → Interpret → Connect to thesis

Checklist

  • Quotes embedded at point of analysis
  • Every claim supported by quote
  • Each quote followed by interpretation
  • Creates "guide through sources"

File Organization

CRITICAL: All tutorials follow this organization pattern:

1. Create in Central Tutorial Directory

# Organize by topic in ~/Desktop/Tutorial
mkdir -p ~/Desktop/Tutorial/{topic-name}

# Create tutorial file there
# Example: ~/Desktop/Tutorial/python-cli/typer-tutorial.md

Topic categories:

  • python-cli/ - CLI tools, Typer, Click, argparse
  • web-apis/ - API tutorials, REST, GraphQL
  • frontend/ - React, JavaScript, HTML/CSS
  • backend/ - Django, Flask, Node.js
  • devops/ - Docker, Kubernetes, CI/CD
  • databases/ - SQL, NoSQL, ORMs
  • tools/ - Git, GitHub, VS Code extensions
  • languages/ - Language-specific guides

2. Create Symlink in Current Directory

# From the project directory, create Tutorial/ directory
mkdir -p Tutorial

# Create symlink to specific tutorial
ln -s ~/Desktop/Tutorial/{topic-name}/{tutorial-name}.md Tutorial/{tutorial-name}.md

# Example:
cd /path/to/gmail-integration-plugin
mkdir -p Tutorial
ln -s ~/Desktop/Tutorial/python-cli/typer-tutorial.md Tutorial/typer-tutorial.md

3. Verify Structure

# Check symlink works
ls -la Tutorial/
# Should show: typer-tutorial.md -> ~/Desktop/Tutorial/python-cli/typer-tutorial.md

# Read through symlink
cat Tutorial/typer-tutorial.md

Why This Pattern?

  1. Centralized tutorials - All tutorials in one place (~/Desktop/Tutorial)
  2. Topic organization - Easy to find related tutorials
  3. Project-specific access - Symlink makes it available in current project
  4. Reusability - Same tutorial can be symlinked from multiple projects
  5. Version control - Symlinks don't clutter git repos (add Tutorial/ to .gitignore)

Workflow

When creating a tutorial:

  1. Determine topic category
  2. Create file in ~/Desktop/Tutorial/{topic}/
  3. Create Tutorial/ directory in current project
  4. Symlink from project to central location
  5. Add Tutorial/ to .gitignore

Tools & Preview

Build: building-artifacts skill (React + Tailwind + shadcn/ui) Format: Dark code blocks with copy buttons, monospace Layout: Sidebar + main content

Preview markdown tutorials:

nvim -c "MarkdownPreview" /path/to/tutorial.md

Use direct commands (no aliases) for reproducibility.