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Semantic Code Search

semantic_code_search
Read-only

Search indexed projects by describing the code logic you need in natural language. Get matching code snippets quickly.

Instructions

Search for code logic across indexed projects using natural language

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language description of what you are looking for
reposNoRestrict search to specific projects
top_kNoNumber of code snippets to return (default: 5)
file_patternNoOptional glob-like filter for filenames
Behavior3/5

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

The readOnlyHint=true annotation already signals a safe read operation, and the description does not contradict that. It adds useful context that projects must be 'indexed' and that the search is semantic, but it does not disclose output format, limitations, or any other behavioral traits. With annotations covering safety, this is adequate but not rich.

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

Conciseness5/5

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

The description is a single sentence with a leading verb, immediately stating what the tool does. It is front-loaded, concise, and contains no filler or repetition.

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

Completeness4/5

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

For a simple read-only search tool with complete schema documentation and a readOnly annotation, the description provides sufficient context. It clearly states the tool searches code logic by natural language, and the schema covers parameters and result count. A minor gap is not describing the output format explicitly, but the top_k parameter implies code snippets, so overall it is fairly complete.

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?

Schema description coverage is 100%, with every parameter (query, repos, top_k, file_pattern) already documented in the schema. The description adds no additional parameter-level meaning, so the baseline score of 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 uses a specific verb ('Search') and resource ('code logic across indexed projects') with the qualifier 'using natural language,' which clearly distinguishes it from sibling tools like search_symbols that search for symbols by name. This is a precise, non-tautological statement of purpose.

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

Usage Guidelines3/5

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

The description implies this is the tool for natural-language, logic-level search across indexed projects, but it gives no explicit when-to-use guidance or mention of alternatives. Sibling tools such as search_symbols and retrieve_context are not referenced, leaving the choice to the agent's inference.

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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