search

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions the tool searches indexed data and is more accurate than training data, but lacks explicit statements about read-only nature, side effects, or caveats like rate limits or result staleness. The schema details parameters, but behavioral context beyond that is minimal.

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

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

The description is two sentences: the first defines the tool's core function, and the second provides strategic usage guidance. Every word is purposeful, no redundancy. It is front-loaded with essential information, making it highly efficient for an agent to parse.

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

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

While the description covers the primary purpose and usage direction, it lacks details about the output format, result structure, or any operational constraints. Given the complexity of 18 parameters and no output schema, the description does not fully fill the gap, but the schema's rich parameter descriptions compensate somewhat.

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

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

Schema description coverage is 100%, so baseline is 3 even if the description adds no parameter-level meaning. The description does not amplify parameter understanding beyond what the schema provides. It introduces no additional semantics for parameters like 'query', 'collection', or 'mode' that would improve agent reasoning.

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

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

The description clearly states the tool performs hybrid semantic and keyword search for documents. It specifies a specific use case: 'Use this tool FIRST when answering questions about the user's codebase, project architecture, or stored knowledge.' This differentiates it from sibling tools like grep or list by emphasizing semantic search and priority.

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

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

The description explicitly advises when to use the tool ('FIRST when answering questions about the user's codebase...') and explains its advantage over training data. However, it does not mention when not to use it or provide alternatives for specific search scenarios, such as when grep would be more appropriate.

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