Search Code Knowledge Graph

Search .gauntlet/graph.db for code entities by name.

When NOT To Use

• The graph is missing or stale (use gauntlet:graph-build)
• Scoring the impact of a change (use pensive:blast-radius)

Steps

1. Accept query: Get the search term from the user.

2. Run the query script:

   python3 ${CLAUDE_PLUGIN_ROOT}/scripts/graph_query.py \
       --action search --query "<term>" --limit 20
   

   Optional filters:

   • --kind Function to search only functions
   • --kind Class to search only classes

3. Display results: Show qualified name, file path, line numbers, and relevance score for each match.

4. Offer to read: Ask if the user wants to read the top result's source file.

Query Intelligence

The search engine detects query patterns:

• PascalCase (e.g., UserService): boosts Class and Type results
• snake_case (e.g., get_users): boosts Function results
• Dotted path (e.g., app.models.User): boosts qualified name matches

Prerequisites

The graph must be built first. If .gauntlet/graph.db does not exist, suggest running the graph-build skill.

Exit Criteria

• If .gauntlet/graph.db does not exist, the skill surfaces the missing-prerequisite error and suggests gauntlet:graph-build rather than failing silently
• Results display qualified name, file path, line numbers, and relevance score for each match (up to --limit results)
• Query intelligence applies correct boost: PascalCase boosts Class/Type results, snake_case boosts Function results, dotted path boosts qualified name matches
• User is offered to read the top result's source file after results are shown
• A count: 0 result is reported as "not in the graph" only after graph_query.py --action status shows node_count above zero. An unbuilt graph, or one built without tree-sitter, answers every query with zero, and that zero says nothing about the codebase