How does it handle recurring issues?

The skill searches for existing similar docs and offers a decision menu to either link related issues or promote the fix to a 'Critical Patterns' list for future reference.

How does Compound Docs detect when to document a problem?

The skill automatically triggers after confirmation phrases like 'that worked' or 'it's fixed,' and can also be manually invoked using the /doc-fix command.

What information is captured in each documentation file?

It captures the module name, symptoms, exact error messages, investigation attempts, technical root cause, the final solution, and prevention steps.

Does it support YAML validation?

Yes, it includes a blocking validation gate that ensures all documentation adheres to a specific YAML schema for consistent categorization and searchability.

Compound Docs

Name: Compound Docs
Author: Activer007

byActiver007

학습 및 문서화

Captures and categorizes solved coding problems into a searchable institutional knowledge base with structured metadata.

소개

The compound-docs skill streamlines technical documentation by automatically identifying when a problem is solved and prompting the creation of metadata-rich records. Using a rigorous 7-step process, it gathers context, validates YAML frontmatter, and organizes solutions into category-based directories. This ensures that debugging insights, root cause analyses, and non-obvious fixes are preserved for future sessions, effectively building a self-organizing knowledge base that prevents the repetition of previous mistakes.

주요 기능

Intelligent category-based organization for logical documentation storage
Strict YAML frontmatter validation for standardized metadata and fast lookup
Pattern detection to promote frequent issues to 'Required Reading' lists
Cross-referencing logic to link related technical issues and solutions
0 GitHub stars
Automatic detection of solved problems via natural conversation triggers

사용 사례

Building a searchable library of root cause analyses for complex legacy systems
Standardizing documentation practices within a development team during active coding sessions
Converting one-off debugging triumphs into reusable patterns for AI-assisted development

소개

주요 기능

Intelligent category-based organization for logical documentation storage
Strict YAML frontmatter validation for standardized metadata and fast lookup
Pattern detection to promote frequent issues to 'Required Reading' lists
Cross-referencing logic to link related technical issues and solutions
0 GitHub stars
Automatic detection of solved problems via natural conversation triggers

사용 사례

Building a searchable library of root cause analyses for complex legacy systems
Standardizing documentation practices within a development team during active coding sessions
Converting one-off debugging triumphs into reusable patterns for AI-assisted development