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cerebro_search

Search codebase using semantic meaning and keyword matches to locate relevant files and return their paths.

Instructions

Find relevant files. When the semantic index is built it ranks by meaning (intent), so phrase queries naturally ("where do we validate stock at checkout?"); it also includes keyword/symbol matches. Returns paths to cerebro_get().

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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 states that the tool ranks by meaning and includes keyword/symbol matches, and returns paths to cerebro_get(). It does not explicitly state whether the tool is read-only or has side effects, but the search nature implies read-only.

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 concise, with three short sentences covering purpose, behavior, and output. It is front-loaded with 'Find relevant files.' and provides an illustrative example. Minor improvement could be to separate the example more clearly.

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

Completeness3/5

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

Given that an output schema exists, the description need not explain return values, but it does indicate paths to cerebro_get(). However, it lacks details on input query format variations, limit behavior, and how to interpret results. It is adequate for basic understanding but not fully 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 coverage is 0%, so the description must compensate. It adds meaning to the 'query' parameter by explaining it can be phrased naturally and includes keyword/symbol matches, with an example. However, the 'limit' parameter is not mentioned, leaving its semantics unclear.

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

Purpose4/5

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

The description clearly states the tool 'Find relevant files' and mentions semantic ranking and keyword/symbol matches. It distinguishes from siblings by explicitly mentioning it returns paths for cerebro_get(), but does not contrast with other search-like siblings (e.g., cerebro_callers).

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 explains when the semantic index is built and how queries work (phrase queries, keyword/symbol matches) with an example. However, it lacks explicit guidance on when to use this tool vs alternatives or when not to use it.

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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