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Deep codebase exploration using semantic search and relationship mapping. Use when you need to understand the current codebase.

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SKILL.md

name codebase-explorer
description Deep codebase exploration using semantic search and relationship mapping. Use when you need to understand the current codebase.
allowed-tools Bash(codanna:*), Bash(sed:*), Bash(rg:*), Read, Grep, Glob

Search Query Analysis

Query Optimization Skill

Codanna's semantic search works best with technical terms and specific concepts. Analyze the situation and optimize your codebase explore queries for code search:

Examples:

  1. If vague (e.g., "that parsing thing") → Make it specific (e.g., "language parser implementation")
  2. If a question (e.g., "how does parsing work?") → Extract keywords (e.g., "parsing implementation process")
  3. If conversational (e.g., "the stuff that handles languages") → Use technical terms (e.g., "language handler processor")
  4. If too broad (e.g., "errors") → Add context (e.g., "error handling exception management")

OptimizedQuery: {Claude: I will write my optimized query here, then use it below}

Execute this command with your optimized query:

Your Workflow

Gather Context

Use the Bash tool to perform semantic code search:

Execute: codanna mcp semantic_search_with_context query:"$OptimizedQuery" limit:5

What Codanna returns:

  • Relevance scores (how well each result matches)
  • Symbol signatures and documentation
  • Relationships (calls, called_by, implements, defines)
  • File locations with line ranges

Your Workflow

  1. Analyze the results with their relevance scores (focus on results with score > 0.6 (if possible))

  2. To see actual implementation of interesting results:

    • Use the line range from the Location field to read just the relevant code
    • Example: If you see "at src/io/exit_code.rs:108-120"
    • Use the Read tool with:
      • file_path: src/io/exit_code.rs (use the working directory from your environment context to construct the absolute path)
      • offset: 108 (start line)
      • limit: 13 (calculated as: 120 - 108 + 1)
    • Formula: limit = end_line - start_line + 1
    • Example: Read(file_path="/full/path/to/src/io/exit_code.rs", offset=108, limit=13)
  3. When relationships are shown (called_by, calls, defines, implements):

    • If a relationship looks relevant to answering the query, investigate it
    • Execute: codanna retrieve describe <relationship_symbol_name|symbol_id:ID>
    • Example: If you see "Called by: initialize_registry [symbol_id:123]", run: codanna retrieve describe initialize_registry or describe symbol_id:123
    • Note: Following 1-2 key relationships per result is typically sufficient
  4. Build a complete picture by following key relationships and reading relevant code sections

  5. If needed, repeat <Step_1: GatherContext> with a refined query based on what you learned.


Tips for Efficient Exploration

The results include:

  • Relevance scores (how well each result matches the query)
  • Symbol documentation and signatures
  • Relationships (who calls this, what it calls, what it defines)
  • System guidance for follow-up investigation

sed (native on unix only):

  • You can also see actual implementation with sed: (works native on Unix based environments):

    • Use the line range from the Location field to read just the relevant code
    • Example: If you see "Location: src/io/exit_code.rs:108-120"
    • Execute: sed -n '108,120p' src/io/exit_code.rs to read lines 108-120
    • This shows the actual code implementation, not just the signature. It works like the Read tool.
  • Add lang:rust (or python, typescript, etc.) to narrow results by language if you work on multi-language projects

  • Follow relationships that appear in multiple results (they're likely important)

  • Use the describe command to get full details about interesting relationships

Token awareness:

  • Each search uses ~500 tokens
  • Each relationship follow uses ~300 tokens
  • Each file read uses ~100-500 tokens (depends on size)
  • Staying efficient keeps your context window clean for deeper analysis

This command is for exploration:

  • Build understanding of the codebase
  • Identify patterns and integration points
  • Present findings and await user direction
  • Don't start implementing or making changes yet

Based on the gathered context, engage with the user to narrow focus and help the user with further request.