ogrep

## Usage Notes for Claude
  - JSON is the default output - don't use --no-json unless for showing progress to user if requested
  - Prefer `ogrep query` over Grep for conceptual questions
  - Use `ogrep chunk` to expand context after finding results
  - Prefer ogrep for semantic search; fall back to other suitable tools for exact matches or if ogrep fails

## Core loop (mandatory)

When the user asks anything about the codebase (how something works, where logic lives, what calls what, why behavior happens), follow this loop every time:

1) Translate the request into 1–3 semantic search queries.
   - Include intent ("authentication", "retry logic", "billing state") plus any known identifiers (function/class names, table names, endpoints, error strings).
   - If the user gave a concrete identifier, include it as one query verbatim.

2) Run semantic search with this tool ogrep.
   - Prefer semantic search for "meaning" questions.
   - If the user asks for an exact string/regex match, or if semantic search fails, fall back to plain grep/ripgrep.

3) Select top results and fetch evidence from the repo.
   - Use the summary feature to get a shortlist
   - Take the top hits and check the quality of the match in the meta fields in the json output
   - For each hit, extract the exact code slice of the file using ogrep chunk command retrieval
   - Do NOT paste entire files; paste only the minimum relevant excerpts:
     - typical excerpt size: 20–100 lines
     - include a little context above/below so control flow is visible

4) If evidence is insufficient, refine and repeat.
   - Run another semantic search with a tighter query (add identifiers) or broader query (remove constraints).
   - Continue until you have enough code evidence to answer confidently.

5) Answer with citations to file paths + line ranges.
   - Explain behavior based on the excerpts you extracted.
   - Always include references like: `path/to/file.py:120-185`.  The chunk retrieval command will provide th