Search generated context

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

With no annotations, the description carries the full burden. It discloses that results are follow-up tool suggestions rather than numerical answers, which is helpful, but it omits other behavioral details such as pagination, response shape, or rate limiting.

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 a single, direct sentence with no filler or redundant information. It is front-loaded with the action and resource.

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?

The description does not explain how to use the filters, what the output format is, or how the tool determines follow-up tools. Given no output schema and no annotations, this is too sparse for a search tool with structured filtering.

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?

The schema has three parameters with 0% description coverage, and the description provides no information about 'query', 'limit', or 'filters'. It fails to compensate for the lack of schema descriptions, leaving parameter semantics entirely undefined.

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 names a specific verb ('Search') and a concrete resource ('compact generated activity, plan, nutrition, and message context') and adds a unique role ('identify authoritative follow-up tools'). This helps differentiate it from sibling data-query tools, though the distinction is not fully explicit.

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 phrase 'rather than making numerical claims' implies this tool is for routing to other tools rather than getting numeric data, but it does not explicitly state when to use this tool versus 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.