Technical Documentation Generator

Overview

Generate comprehensive technical documentation by analyzing the actual codebase. Produces API references, architecture overviews, getting started guides, and component documentation with real examples extracted from project code, not invented ones.

Announce at start: "I'm using the tech-docs-generator skill to create documentation."

Phase 1: Codebase Analysis

Scan the codebase to identify what needs documenting. Deploy parallel subagents via the Agent tool (up to 500, with subagent_type="Explore") to analyze:

Analysis Target	What to Capture
Exported functions/classes	Public API surface, signatures, return types
API routes/endpoints	REST, GraphQL, tRPC definitions with methods
Configuration	Env vars, config files, feature flags
Database schemas	Models, migrations, relationships
Component hierarchy	UI components and their props/interfaces
Type definitions	Interfaces, types, Zod schemas, enums
Entry points	CLI commands, main files, server bootstrap
Dependencies	External packages and their roles

STOP after analysis — present a summary of what was found and ask which documentation types are needed.

Phase 2: Documentation Type Selection

Type	When to Use	Output Path	Typical Size
API Reference	Documenting endpoints or public functions	docs/api-reference.md	200-1000 lines
Architecture Overview	Explaining system design and data flow	docs/architecture.md	100-300 lines
Getting Started	Onboarding new developers	docs/getting-started.md	50-150 lines
Component Docs	Documenting UI components	docs/components/[name].md	50-200 lines
Contributing Guide	Explaining how to contribute	docs/contributing.md	50-100 lines
Configuration Guide	Documenting config options	docs/configuration.md	50-200 lines
Migration Guide	Documenting version upgrades	docs/migration/v[X]-to-v[Y].md	50-150 lines

Ask the user which type(s) they need if not specified. If multiple types are requested, dispatch parallel subagents via the Agent tool — one per doc type.

Phase 3: Generate Documentation

Dispatch doc-generator agent with:

• File analysis results from Phase 1
• Documentation type selected in Phase 2
• Existing documentation (to update, not replace)
• Project context from memory files

STOP after generation — present each section for review before saving.

Documentation Format Standards

API Reference format:

## `functionName(param1, param2)`

Description of what this function does.

**Parameters:**
| Name | Type | Required | Description |
|------|------|----------|-------------|
| param1 | `string` | Yes | What it does |
| param2 | `Options` | No | Configuration options |

**Returns:** `Promise<Result>`

**Example:**
```typescript
const result = await functionName('value', { option: true });

Throws: ValidationError if param1 is empty

**Architecture Overview format:**

```markdown
## System Architecture

### Overview
[High-level description with ASCII diagram]

### Components
| Component | Responsibility | Key Files |
|-----------|---------------|-----------|

### Data Flow
[How data moves through the system — request lifecycle]

### Key Decisions
| Decision | Rationale | Alternatives Considered |
|----------|-----------|------------------------|

Getting Started format:

## Prerequisites
[Required tools, versions, accounts]

## Installation
[Step-by-step with copy-pasteable commands]

## Configuration
[Required env vars and config]

## First Run
[How to start the app and verify it works]

## Next Steps
[Links to deeper documentation]

Phase 4: Review and Save

Present documentation section by section:

1. Ask after each section: "Does this accurately describe the code?"
2. Cross-reference with actual code to verify accuracy
3. Include real examples from the codebase — never invented ones
4. After approval, save to docs/ directory
5. Commit with message: docs(<scope>): add/update <doc-type>

Accuracy Verification Checklist

Check	How to Verify
Function signatures match code	Read the source file
Examples actually work	Trace the code path
Config options are current	Check actual config files
Dependencies listed are installed	Check package.json / requirements
File paths referenced exist	Glob for the files

Anti-Patterns / Common Mistakes

Mistake	Why It Is Wrong	What To Do Instead
Inventing code examples	Readers copy-paste and get errors	Extract real examples from the codebase
Documenting internal/private APIs	Creates coupling to implementation	Only document public/exported surface
Writing docs that duplicate source code	Goes stale immediately	Reference behavior, not implementation
Giant monolithic doc file	Hard to navigate and maintain	Split by concern (API, architecture, config)
Documenting aspirational behavior	Misleads users about current capabilities	Document what actually works today
Skipping the analysis phase	Miss important APIs or get signatures wrong	Always analyze code first
Not verifying examples compile/run	Broken docs worse than no docs	Test every code example

Anti-Rationalization Guards

• Do NOT generate documentation without first analyzing the actual code
• Do NOT invent examples — every code snippet must come from or be verified against the codebase
• Do NOT document private/internal APIs unless explicitly requested
• Do NOT skip the review phase — present each section for user verification
• Do NOT duplicate information already covered in other docs — reference instead

Integration Points

Skill	Relationship
prd-generation	Upstream: PRD defines what needs documenting
self-learning	Parallel: both analyze codebase; self-learning populates memory files used here
api-design	Upstream: API design specs inform API reference docs
spec-writing	Parallel: specs define behavior; docs explain usage
reverse-engineering-specs	Upstream: reverse-engineered specs provide behavioral understanding
code-review	Downstream: reviewer checks if docs were updated alongside code changes

Verification Gate

Before claiming documentation is complete:

1. VERIFY all public APIs are documented with correct signatures
2. VERIFY code examples actually work (not invented)
3. VERIFY cross-references link to existing content
4. VERIFY documentation matches current code state
5. VERIFY the user has approved each section
6. RUN any documented commands to confirm they work

Concrete Example: API Reference Entry

Given this source code:

export async function createUser(data: CreateUserInput): Promise<User> {
  // validates, hashes password, inserts into DB
}

Generate this documentation:

## `createUser(data)`

Create a new user account with the provided details.

**Parameters:**
| Name | Type | Required | Description |
|------|------|----------|-------------|
| data | `CreateUserInput` | Yes | User registration data |

**`CreateUserInput` shape:**
| Field | Type | Required | Constraints |
|-------|------|----------|-------------|
| email | `string` | Yes | Valid email format |
| password | `string` | Yes | Minimum 8 characters |
| name | `string` | Yes | 1-100 characters |

**Returns:** `Promise<User>` — the created user object (password excluded)

**Throws:**
- `ValidationError` — if input fails validation
- `ConflictError` — if email already exists

Skill Type

Flexible — Adapt documentation depth and format to project needs while preserving the analyze-first principle and accuracy verification.