Does it support team-wide knowledge sharing?

Yes, by organizing files into a standard directory structure with consistent metadata, it creates a searchable knowledge base that any team member can query using grep or file search.

How does the skill know when to start documenting?

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

What kind of metadata is captured in the documentation?

It captures specific module names, exact error messages, investigation attempts, technical root causes, and environment details like OS and framework versions.

Can I prevent it from documenting trivial fixes?

Absolutely. The skill is designed to skip simple typos or obvious syntax errors, focusing instead on non-trivial debugging that provides long-term value.

What happens if a similar problem has already been documented?

The skill searches existing documentation and presents a decision menu to either create a cross-referenced new document or update the existing entry if the root cause is the same.

Compound Problem Documentation

Name: Compound Problem Documentation
Author: Microck

byMicrock

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学习与文档

Captures solved technical problems as structured, searchable documentation with validated YAML metadata for rapid knowledge retrieval.

关于

Compound Problem Documentation is a specialized skill designed to transform transient debugging sessions into permanent institutional knowledge. It automatically detects when a problem has been solved and guides the developer through a structured 7-step process to document the root cause, symptoms, and resolution. By enforcing a strict YAML schema and category-based organization, it ensures that all solutions are easily searchable and formatted for future reuse. This skill is particularly valuable for complex projects where recurring patterns need to be identified and promoted to critical 'Required Reading' to prevent future regressions.

主要功能

Automatic invocation based on conversation success markers or manual commands
81 GitHub stars
Automated categorization of solutions based on validated problem types
Strict YAML schema validation to ensure consistent and searchable metadata
Pattern detection system to promote recurring fixes to critical project guidelines
Integrated cross-referencing between related technical issues and existing skill sets

使用场景

Building a searchable 'lessons learned' database for complex legacy codebases
Standardizing bug reporting and resolution documentation across a development team
Identifying and institutionalizing critical architectural patterns to avoid repeat errors

关于

主要功能

Automatic invocation based on conversation success markers or manual commands
81 GitHub stars
Automated categorization of solutions based on validated problem types
Strict YAML schema validation to ensure consistent and searchable metadata
Pattern detection system to promote recurring fixes to critical project guidelines
Integrated cross-referencing between related technical issues and existing skill sets

使用场景

Building a searchable 'lessons learned' database for complex legacy codebases
Standardizing bug reporting and resolution documentation across a development team
Identifying and institutionalizing critical architectural patterns to avoid repeat errors