Search project context and learnings using fuzzy matching.
npx skills add https://github.com/paxtone-studio/openkodo --skill query-paxtone-studio
Please help me install this Agent Skill. Skill: query Source: https://github.com/paxtone-studio/openkodo/tree/main/plugins/kodo/skills/query Command: npx skills add https://github.com/paxtone-studio/openkodo --skill query-paxtone-studio
This Skill helps you quickly find relevant information within your project's accumulated knowledge base, preventing redundant work and ensuring consistency.
Use the query skill to search for information about error handling in the project context.
High-intent search queries and answers about installing and using this skill.
You can search accumulated project context and learnings by using fuzzy matching to retrieve relevant architectural patterns, technical notes, and past decisions. This ensures consistency and prevents redundant work during development.
To retrieve architectural patterns, query the knowledge base using fuzzy search. This allows you to find existing solutions and established practices, ensuring you build upon past technical decisions before implementing new features.
Yes, you can find codebase learnings with typos or variations by using fuzzy search. This mechanism matches slight variations in your search terms to accurately retrieve relevant technical notes and project context.
You can filter project knowledge base search results by category, time, or confidence level. This narrows down the retrieved information, helping you quickly access specific architectural patterns or technical notes.
You should query existing context before making design choices to satisfy the need for efficient knowledge retrieval. This ensures consistency checks are performed, allowing you to inform current development with established practices and past decisions.
resolve-ioStore project context as Obsidian markdown notes with YAML frontmatter.
vib795Detect drift between documented learnings and current code, then refresh affected pattern docs.
WalliieeSearch local markdown knowledge bases with hybrid keyword and semantic retrieval.
HuuBarSearch large documents using exact, normalized, and fuzzy n-gram matching.
