Pre-load relevant wiki context to ground architectural answers during subsystem exploration.
npx skills add https://github.com/ImLp/claude-caide --skill recall-imlp
Please help me install this Agent Skill. Skill: recall Source: https://github.com/ImLp/claude-caide/tree/main/.claude/skills/recall Command: npx skills add https://github.com/ImLp/claude-caide --skill recall-imlp
Recall addresses the knowledge gap when exploring large codebases by pre-loading the most relevant wiki context to ground answers and reduce hallucinations.
Initiate a recall by typing /recall followed by an optional topic to preload the most relevant wiki context for your current focus.
High-intent search queries and answers about installing and using this skill.
Pre-loading wiki context reduces hallucinations by surfacing relevant architectural facts before answering. The recall skill runs at session start or focus switches, reading loaded pages to ground responses with module roles, dependencies, and ADR status.
Semantic search for loading architectural context uses qmd to find and pre-load the most relevant wiki pages. When qmd is unavailable, it falls back to reading wiki/index.md to gather available subsystem documentation.
Grounding architectural answers requires summarizing loaded wiki context to surface key facts like module roles and dependencies. The recall skill identifies gaps in documentation and notes them for follow-up before providing a response.
Yes, you can load context for a specific topic at session start by typing /recall followed by the optional topic. This pre-loads the most relevant wiki pages to align responses with your current focus area.
You do not need qmd installed to use the recall skill for session management. It uses qmd semantic search when available but automatically falls back to wiki/index.md to load relevant architectural context.
Falling back to wiki/index.md without qmd semantic search limits context loading to manual index traversal rather than semantic matching. The skill still summarizes available page content and notes documentation gaps, but may lack deep relevance ranking.
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