Documentation

Documentation

You are generating or updating technical documentation for this project using structured writing principles.

Red Flags — STOP if you're:

• Writing docs without reading the code first
• Duplicating information that exists elsewhere (link instead)
• Writing docs for internal implementation details (only public interfaces)
• Ignoring the target audience (developer vs operator vs new hire)
• Generating a wall of text without structure or examples

Write for the reader. Link don't duplicate. Show don't tell.

Pre-Check

1. Check for Draft context:

ls draft/ 2>/dev/null

If draft/ doesn't exist, this skill works standalone — generate docs from code analysis.

2. Follow the base procedure in core/shared/draft-context-loading.md.

Step 1: Parse Arguments

• /draft:documentation readme — Generate or update project README
• /draft:documentation runbook <service> — Operations runbook for a service
• /draft:documentation api <module> — API documentation for a module
• /draft:documentation onboarding — New developer onboarding guide
• /draft:documentation (no args) — Interactive: ask what type of documentation

Step 2: Gather Source Material

README Mode

• Read existing README.md (if any)
• Read draft/product.md — Product vision, users, goals
• Read draft/tech-stack.md — Technologies, setup requirements
• Read draft/workflow.md — Development workflow, commands
• Scan for Makefile, package.json, pyproject.toml — Build/run commands

Runbook Mode

• Read draft/architecture.md or draft/.ai-context.md — Service topology, dependencies
• Read draft/workflow.md — Deployment conventions
• Read draft/tech-stack.md — Infrastructure details
• If GitHub MCP available: check recent deployment changes
• If Jira MCP available: check recent incident tickets for the service

API Mode

• Read source code for public interfaces, exported functions, API routes
• Read existing API docs (Swagger, OpenAPI, JSDoc, docstrings)
• Read draft/architecture.md — API conventions, data models
• Read draft/tech-stack.md — API framework details

Onboarding Mode

• Read ALL draft context files in order:
  1. draft/product.md — What is this project?
  2. draft/tech-stack.md — What technologies?
  3. draft/architecture.md or draft/.ai-context.md — How is it structured?
  4. draft/workflow.md — How do I develop?
  5. draft/guardrails.md — What to watch out for?
• Scan for setup scripts, Docker configs, environment templates

Step 3: Apply Writing Principles

Follow these principles (from core/agents/writer.md):

1. Write for the reader — Identify the audience (developer, operator, new hire) and tailor language, depth, and examples accordingly
2. Start with the most useful information — Lead with what the reader needs most (setup for README, troubleshooting for runbook, endpoints for API)
3. Show don't tell — Use code examples, command snippets, and diagrams over prose descriptions
4. Progressive disclosure — Start simple, add detail progressively. Don't front-load every edge case
5. Link don't duplicate — Reference existing docs, don't copy them. Single source of truth
6. Keep current — Reference source of truth files. Note: "Generated from draft context on {date}"

Step 4: Generate Document

README Structure

# {Project Name}

{One-line description from product.md}

## Quick Start
{Setup commands from Makefile/package.json}

## Architecture
{High-level diagram from .ai-context.md}

## Development
{Commands from workflow.md}

## Testing
{Test commands and conventions}

## Contributing
{Workflow conventions}

Runbook Structure

# Runbook: {Service Name}

## Overview
{Service purpose, dependencies, SLOs}

## Health Checks
{Endpoints, expected responses}

## Common Issues
{Symptoms → diagnosis → resolution}

## Deployment
{Steps, rollback procedure}

## Monitoring
{Dashboard URLs, alert descriptions}

## Escalation
{On-call contacts, escalation paths}

API Documentation Structure

# API: {Module Name}

## Overview
{Purpose, authentication, base URL}

## Endpoints

### {METHOD} {path}
{Description}
**Request:** {body/params with examples}
**Response:** {status codes with examples}
**Errors:** {error codes and meanings}

Onboarding Structure

# Welcome to {Project Name}

## What is this?
{From product.md — 2-3 sentences}

## Architecture at a Glance
{Simplified from .ai-context.md}

## Getting Started
{Setup steps, first 15 minutes}

## Key Concepts
{Domain terms, important patterns}

## Development Workflow
{From workflow.md}

## Where to Find Things
{File structure guide}

## Common Pitfalls
{From guardrails.md}

Step 5: Output

Save to:

• README: README.md in project root
• Runbook: draft/docs/runbook-<service>.md
• API: draft/docs/api-<module>.md
• Onboarding: draft/docs/onboarding.md

Create draft/docs/ directory if needed.

Pre-save validation:

• Every file path referenced in the doc resolves to a real file (broken links are a common LLM failure mode here).
• Every relative link in the doc resolves under the project root.
• Code blocks copied from sources match the current commit (no stale snippets).

Present generated doc to user for review before final save.

Cross-Skill Dispatch

• Suggested by: /draft:init (after context generation), /draft:implement (track completion with new APIs), /draft:upload (pre-upload for new APIs), /draft:decompose (module API docs)
• Jira sync: If ticket linked, attach doc and post comment via core/shared/jira-sync.md

Error Handling

If no draft context: Generate from code analysis alone, note: "Run /draft:init for richer documentation" If existing doc found: Show diff between existing and generated, ask: "Update existing doc or create new? [update/new]"

Source: mayurpise/draft — distributed by TomeVault.