/x-ray

Search Query Analysis

User's Original Query: "$ARGUMENTS"

Query Optimization

Codanna's semantic search works best with technical terms and specific concepts. Analyze the query above and improve it for code search:

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: Write your improved query here, then use it below}

Execute this command with your optimized query:

Your Workflow <Workflow>

Gather Context <Step_1 GatherContext>

Use the Bash tool to perform semantic code search:

Execute: node .claude/scripts/codanna/context-provider.js find "$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 <Step_2 YourWorkflow>

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 "Location: 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 <env> 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: node .claude/scripts/codanna/context-provider.js describe <relationship_symbol_name|symbol_id:ID>
   • Example: If you see "Called by: initialize_registry [symbol_id:123]", run: node .claude/scripts/codanna/context-provider.js 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.

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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.