Intelligent Code Search with WarpGrep

WarpGrep is an RL-trained search agent that reasons about code, not just pattern matches. Use zoom-out mode when the user needs a higher-level map before touching code.

How It Works

• 8 parallel searches per turn (explores multiple hypotheses)
• 4 reasoning turns (follows causal chains across files)
• F1=0.73 in ~3.8 steps (vs 12.4 for standard search)

When to Use Which Tool

Use WarpGrep	Use Smart Explore (claude-mem)	Use Built-in Grep
"How does auth flow work?"	"What functions are in this file?"	"Find class UserService"
"Trace data from API to DB"	"Show me this function's source"	Simple regex patterns
"Find all error handling"	"Find all types matching X"	"Where is X defined?"
Large repos (1000+ files)	File structure at a glance	Known file patterns
Before major refactoring	Targeted function extraction	Quick needle lookups

When available, prefer Smart Explore for structural queries (10-20x fewer tokens). Use WarpGrep for semantic/reasoning queries across files.

Query Formulation

Good queries (reasoning required):

"How does authentication flow from the login handler to the database?"
"Find all places where user permissions are checked"
"Trace the request lifecycle from router to response"

Bad queries (use Grep instead):

"Find UserService" → use Grep
"Search for 'import React'" → use Grep

Workflow

1. Formulate query: Describe WHAT you want to understand, not just WHAT to find
2. Load domain docs when present: CONTEXT.md, CONTEXT-MAP.md, and relevant ADRs
3. Run WarpGrep: mcp__morphllm__warpgrep_codebase_search
4. Interpret results: Ranked snippets with file paths and line numbers
5. Follow up: Read specific files for deeper understanding

Zoom-Out Mode

Use when the user says "zoom out", "map this area", "go up a layer", or sounds lost in local details.

Return a map, not a dump:

• relevant modules and callers
• data/control flow across seams
• domain terms from CONTEXT.md
• ADR constraints that shape the design
• where to read next, limited to the top 3 files

Avoid line-by-line explanations unless asked. The point is orientation, not drowning the user in snippets.

Parameters

search_string: "natural language description of what to find"
repo_path: "/absolute/path/to/repo"

Tips

• Be specific about the behavior or flow you're investigating
• Include context: "in the API layer" or "during startup"
• WarpGrep handles ambiguity better than exact pattern matching
• Results include surrounding context for understanding