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

Annotations already indicate read-only and closed-world behavior. The description adds the valuable context that the search is 'deep' and scans multiple facets (paths, operations, parameters), going beyond simply listing endpoints. It doesn't disclose performance limits, but given the annotations, this is sufficient.

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?

Three concise sentences, each providing unique value: what it does, when to use it, and how results connect to 'get-endpoint.' No fluff or repetition.

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?

For a simple one-parameter search tool with read-only annotations, the description covers purpose, usage, and a concrete next step. It would be slightly stronger if it hinted at result format or size, but the mention of passing results to 'get-endpoint' implies compatibility, which is adequate.

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 coverage is 100% with a single parameter 'pattern' clearly described as case-insensitive. The description adds no new param semantics beyond calling it 'keywords,' so it stays at the baseline 3.

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 uses a specific verb ('deep search') and clearly identifies the resource ('API endpoints') and the scope ('paths, operations, and parameters'). It distinguishes itself from sibling tools like 'list-endpoints' by emphasizing search across multiple dimensions.

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?

Explicitly states when to use: 'to find specific API capabilities, required parameters, or data models based on search keywords.' While it doesn't list alternatives or when-not-to-use, the use case is clear and it suggests a direct workflow with 'get-endpoint.'

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