What does the Opi skill do?

It analyzes your recent work to identify and document lessons learned, helping Claude avoid repeating the same mistakes in the future.

Why is it called 'Opi'?

The name 'Opi' is derived from the Finnish word for 'learn', reflecting its core mission of capturing knowledge from development activities.

Where are the learnings stored?

Learnings are stored in Markdown files within your repository, such as .claude/LEARNINGS.md or specific reference files in skill directories.

How does it identify what to extract?

It scans git commit messages for keywords like 'fix' or 'refactor', examines code diffs, and reviews your conversation history for manual corrections.

Can I review the learnings before they are saved?

Yes, the skill presents a list of proposed learnings for you to approve, reject, or modify before any files are written to disk.

Knowledge & Learning Extractor

Name: Knowledge & Learning Extractor
Author: majiayu000

bymajiayu000

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学习与文档

Extracts actionable insights from git history and conversations to build a persistent project memory for Claude.

关于

The Opi skill helps developers maintain a 'living memory' of their project by analyzing recent git commits, refactors, and chat history to identify non-obvious patterns, fixes, and best practices. It streamlines the post-session reflection process by automatically categorizing learnings—such as TypeScript patterns, CI/CD fixes, or specific library quirks—and proposing updates to documentation files, ensuring that future AI interactions are more context-aware and efficient by avoiding repeated mistakes.

主要功能

64 GitHub stars
Automated Git commit analysis for bug fixes and refactors
Conversation history scanning for user corrections and non-obvious solutions
Standardized 'Right vs. Wrong' pattern formatting for actionable documentation
Interactive approval workflow for proposed knowledge updates
Smart categorization of learnings across global or skill-specific files

使用场景

End-of-session reflection to capture technical discoveries and project patterns
Building a project-specific knowledge base to reduce repeated AI errors
Documenting complex library quirks or CI/CD fixes discovered through trial and error

关于

主要功能

64 GitHub stars
Automated Git commit analysis for bug fixes and refactors
Conversation history scanning for user corrections and non-obvious solutions
Standardized 'Right vs. Wrong' pattern formatting for actionable documentation
Interactive approval workflow for proposed knowledge updates
Smart categorization of learnings across global or skill-specific files

使用场景

End-of-session reflection to capture technical discoveries and project patterns
Building a project-specific knowledge base to reduce repeated AI errors
Documenting complex library quirks or CI/CD fixes discovered through trial and error