iterative-retrieval

# Iterative Retrieval ## Overview In large code bases, one search is often not enough. This skill iterates through a search loop, gradually narrowing the scope and pinpointing the relevant code. ## When to Activate - Research requires multiple searches because the first result set is incomplete or low-confidence. - A claim depends on current external documentation, issue state, API behavior, or release notes. - Search results disagree and need a refinement loop before conclusions are trusted. - A task needs fact/inference separation before implementation or recommendation. - A first search returns too many partially related results or misses the target surface. - A codebase question spans file names, symbols, docs, and generated artifacts. - A user needs evidence-backed repository orientation before implementation. ## Red Flags - The same broad query is repeated without changing terms or scope. - Low-relevance results are read in depth before high-relevance anchors. - Search history is lost, so later conclusions cannot be traced back to evidence. ## Checklist - [ ] Start with 2-3 concrete keywords from the user request. - [ ] Score search results before expanding into neighboring files. - [ ] Stop after three rounds with an explicit unresolved-questions list. ## 4 stage cycle ### 1. DISPATCH (distribution search) - Extract search keywords from requirements - Choose a search strategy: - Glob: Search by filename pattern - Grep: search by content keywords - AST:...