find

Code Search

Find code using natural language. Automatically routes to the right search backend.

Steps

1. Parse the user's query:

   • If the user provided a query argument, use it directly
   • Otherwise, ask what they're looking for

2. Call find_code with the query:

   • Let focus default to auto
   • If the user mentioned a specific directory or package, pass it in paths
   • If the user wants test files included, set include_tests: true
   • If the user is debugging search quality, set debug: true

3. Interpret the results based on confidence:

   High confidence (strong matches from multiple sources):

   • Show the top 3 candidates with file path, symbol name, and why it matched
   • For the #1 candidate, show the snippet and enclosing function/component
   • If the result has graph evidence, mention what was promoted/demoted
   • Automatically call gather_context on the #1 candidate's symbol to provide ready-to-use context

   Medium confidence (reasonable matches, single source):

   • Show top 3 candidates with evidence
   • Suggest the user refine their query or try a more specific term
   • Offer to run find_pattern if the query has a structural shape
   • Note any warnings (scope capped, partial results)

   Low confidence (weak or no matches):

   • Explain what was searched and why it didn't match well
   • Check the IR: suggest using the exact function name if only NL tokens were used
   • Offer to try find_pattern with an AST pattern instead
   • If scope was capped, mention it and suggest narrowing with paths

4. Offer follow-up actions:

   • "Want me to read the top result?" → Read the file
   • "Want more context?" → Call gather_context on the top candidate's symbol
   • "What calls this?" → Call call_hierarchy on the symbol
   • "What breaks if I change this?" → Call impact_trace on the symbol
   • "Is the API safe?" → Call api_guard on the file

5. If stats.partialResult is true or warnings is non-empty, mention it clearly so the user knows the search was incomplete.