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mrorigo
by mrorigo

semantic_search

Search codebase using vector similarity to find relevant code snippets based on semantic meaning, with optional filters and output formatting.

Instructions

Perform semantic search in codebase using vector similarity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query string
formatNoOutput format: 'markdown' or 'json'markdown
filtersNoOptional filters to apply to the search results
n_resultsNoNumber of results to return

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes
analysis_statusNo
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It only mentions the high-level function without disclosing behaviors like rate limits, authentication needs, or what happens with empty results. Basic transparency is lacking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single efficient sentence (7 words) with no redundancy. It is concise, though perhaps too brief for full clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 4 parameters, nested objects, and an output schema, the description is very minimal. It does not explain what 'semantic search' entails, how filters work, or what the output contains. More context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% description coverage, so the description adds no value beyond what the schema already provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs 'semantic search' in a 'codebase' using 'vector similarity', which is a specific verb+resource. It distinguishes it from sibling tools like check_drift or get_call_graph.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives (e.g., get_function_metadata), nor any exclusions or prerequisites. The description only states what it does, not when it's appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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