Does it prevent duplicate documentation?

Yes, the skill includes a search step that checks for existing solutions, allowing you to cross-reference new docs or update existing ones if the root cause is identical.

What format is the documentation stored in?

Documentation is stored as single markdown files within categorized directories, featuring validated YAML frontmatter for fast metadata lookups and searchability.

When does the compound-docs skill trigger?

The skill triggers automatically after detecting phrases like 'it's fixed' or 'problem solved,' or it can be invoked manually using the /doc-fix or /compound commands.

What is the 'Required Reading' feature?

This feature allows users to promote critical patterns or recurring mistakes to a central file that subagents can review before generating new code, ensuring best practices are followed.

Compound Documentation

Name: Compound Documentation
Author: Microck

byMicrock

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Content Management

Captures and organizes verified problem solutions into a searchable, categorized knowledge base using structured markdown and YAML frontmatter.

About

The compound-docs skill streamlines institutional knowledge building by automatically transforming solved technical issues into standardized documentation. Triggered by confirmation phrases or manual commands, it guides Claude through a rigorous 7-step process—from context gathering and YAML validation to cross-referencing existing entries. This ensures that tricky debugging sessions, non-obvious fixes, and root cause analyses are preserved in a consistent format, preventing the repetition of past mistakes and providing a 'Required Reading' layer for future development sessions.

Key Features

Cross-referencing and critical pattern detection for recurring issues
Automated detection of successful fixes to prompt documentation capture
Post-capture decision menu to promote entries to 'Required Reading' or new skills
Strict YAML frontmatter validation for consistent metadata and searchability
Categorized file organization based on enum-validated problem types
81 GitHub stars

Use Cases

Standardizing how teams document non-obvious solutions and technical debt
Creating a 'lessons learned' database during major architectural migrations
Building a searchable repository of complex bug fixes for large codebases

About

Key Features

Cross-referencing and critical pattern detection for recurring issues
Automated detection of successful fixes to prompt documentation capture
Post-capture decision menu to promote entries to 'Required Reading' or new skills
Strict YAML frontmatter validation for consistent metadata and searchability
Categorized file organization based on enum-validated problem types
81 GitHub stars

Use Cases

Standardizing how teams document non-obvious solutions and technical debt
Creating a 'lessons learned' database during major architectural migrations
Building a searchable repository of complex bug fixes for large codebases