📚 Skill: docs-pro (v1.1.0)

Executive Summary

docs-pro is a comprehensive skill for managing the lifecycle of technical documentation. It bridges the gap between raw implementation and user-facing clarity. In 2026, we treat Documentation as Code (DaC), using AI to ensure that every new feature, configuration, and API change is accurately reflected in our docs within minutes of a commit.

📋 Table of Contents

1. Core Capabilities
2. The "Do Not" List (Anti-Patterns)
3. Quick Start: The Sync Audit
4. Standard Production Patterns
5. Documentation Quality Standards
6. AI-Driven Documentation Workflow
7. Reference Library

🚀 Core Capabilities

• Automated Sync Audit: Scanning codebases for undocumented exports, settings, and flags.
• Style Enforcement: Ensuring all documentation follows the 2026 Squaads AI Style Guide.
• Modular Content Architecture: Managing reusable snippets and modular pages for scalability.
• Multimodal Documentation: Integrating diagrams (Mermaid), code examples, and interactive elements.

🚫 The "Do Not" List (Anti-Patterns)

⚡ Quick Start: The Sync Audit

Perform a basic check to see what's missing in your documentation:

# 1. Analyze changes in current branch vs main
git diff main...HEAD -- src/

# 2. Search for common undocumented patterns
rg "export (const|function|class)" src/ --type ts

# 3. Compare findings with docs/ structure
ls -R docs/

🛠 Standard Production Patterns

Pattern A: The Feature Release Doc

When implementing a new feature, follow this checklist:

1. Overview: What does it do?
2. Configuration: List all environment variables and settings.
3. Examples: Provide "Quick Start" and "Advanced" code blocks.
4. Troubleshooting: Common errors and their fixes.

Pattern B: The API Reference Update

Instead of editing docs/ref/*.md directly:

1. Update the JSDoc/TSDoc comments in the source code.
2. Run the doc generator (e.g., make build-docs).
3. Verify the output matches the Markdown Standard.

📏 Documentation Quality Standards

We adhere to strict standards to ensure high utility for both humans and AI agents.

• Clarity: Active voice, present tense, and direct address.
• Accuracy: Code examples must be tested and valid.
• Discoverability: Every page must be listed in mkdocs.yml with a descriptive title.

See References: Style Guide for more.

🤖 AI-Driven Documentation Workflow

1. Inventory: AI scans the codebase to build a feature list.
2. Gap Analysis: AI compares the inventory to existing .md files.
3. Drafting: AI proposes new content based on implementation logic.
4. Review: Human-in-the-loop verification of tone and accuracy.

See References: AI Collaboration for more.

📖 Reference Library

Detailed deep-dives into documentation excellence:

• 2026 Style Guide: Voice, tone, and structural rules.
• Markdown Standards: Frontmatter, code blocks, and AI-friendly syntax.
• AI Collaboration Guide: How agents and humans work together on docs.
• Coverage Checklist: The master list for doc audits.

Updated: January 22, 2026 - 17:05