codebase-search

Semantic local search powered by MorphLLM — an RL-trained subagent that runs ~15-30 internal grep+read operations to answer natural language questions about any project files (code, config, docs, markdown, YAML, JSON, and other text files). Unlike simple grep, it understands intent and traces cross-file flows.

Requires MORPH_API_KEY environment variable.

When to Use

• Understanding how a feature works across multiple files (e.g., "how does the auth middleware validate tokens?")
• Tracing data flow end-to-end (e.g., "what happens when a user clicks checkout?")
• Exploring unfamiliar projects where you don't know what to grep for
• Answering architectural questions (e.g., "how is the database layer organized?")
• Debugging cross-file interactions where the connection isn't obvious
• Finding information in non-code files — config, docs, markdown, YAML, JSON (e.g., "how are the plugin hooks configured?")

When NOT to Use

• Simple keyword or symbol searches (e.g., finding all uses of handleSubmit) — use Grep
• Finding files by name or pattern — use Glob
• Looking up library documentation — use context7
• Questions unrelated to the current codebase

Decision Rule

Can you write the grep pattern yourself? Use Grep — it's faster. Can't write the pattern because the question is conceptual? Use codebase-search.

Task	Tool
Find all imports of AuthService	Grep
How does AuthService validate tokens?	codebase-search
Find files named *.config.ts	Glob
How is the config system structured?	codebase-search
Find TODO comments	Grep
What's left unfinished in the payment flow?	codebase-search

Workflow

DO NOT read script source code. Run scripts directly and use --help for usage.

Run a Semantic Search

python3 scripts/codebase-search.py search "<natural language query>" [repo_path]

• query — a natural language question about the code
• repo_path — path to the repo root (defaults to current directory)

# Search the current repo
python3 scripts/codebase-search.py search "how does the authentication flow work"

# Search a specific repo
python3 scripts/codebase-search.py search "how are database migrations handled" /path/to/repo

# Search including node_modules
python3 scripts/codebase-search.py search "how does the router resolve paths" --search-type node_modules

# Increase timeout for large codebases
python3 scripts/codebase-search.py search "trace the payment processing pipeline" --timeout 180

Run python3 scripts/codebase-search.py --help for full usage.

Example Output

Morph Fast Context subagent performed search on repository:

Relevant context found:
- plugins/ora/agents/ariadne.md:*
- plugins/ora/agents/clio.md:*
- plugins/ora/agents/metis.md:*

Here is the content of files:

<file path="plugins/ora/agents/ariadne.md">
1| ---
2| name: Ariadne
3| description: |
4|   Use this agent to explore and understand codebases...
...
35| tools: ["Read", "Glob", "Grep", "LSP", "Bash"]
36| skills:
37|   - codebase-search
38| ---
</file>

<file path="plugins/ora/agents/clio.md">
1| ---
2| name: Clio
...
</file>

The output lists relevant files found and their full content. Use these results directly — do not re-search the same files with Grep/Read.

Rules

• Write queries as natural language questions — "How does the auth middleware validate JWT tokens?" works far better than "auth JWT", because codebase search is an RL-trained agent that plans its own search strategy based on your question.
• Be specific about what you want to know — "What happens when a user submits the settings form?" beats "settings form". The more context you give, the better it can target its internal searches.
• Use for understanding, not for finding — If you already know the symbol or keyword, Grep is faster. codebase-search shines when you don't know what to look for.
• Default timeout is 120s — codebase search runs many internal operations. For large codebases, increase with --timeout 180 or higher.