kasko_search_archive

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

Annotations already provide readOnlyHint: true and openWorldHint: true, indicating a safe, read-only operation with potentially expanding data. The description adds value by explaining that the spreadsheet is downloaded and filtered server-side, which implies a delayed response and potential size limits. It also clarifies the historical scope limitation, which is not in the annotations.

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 very concise: two sentences covering purpose, use case, and a behavioral caveat. Every sentence provides essential information without redundancy. The layout is front-loaded with the core action, making it easy for an AI agent to quickly grasp the tool's role.

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?

Given the tool's complexity (4 parameters, 2 required, no enums) and the presence of a full input schema and output schema, the description is complete enough. It explains the historical query purpose, the server-side processing behavior, and advises on query specificity. The annotations fill in safety and scope, and the sibling tools provide alternatives for other use cases.

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%, so each parameter has a description. The description adds meaning by clarifying that 'query' is an optional free text filter for brand and model names, which is consistent with the schema. While the schema already provides details, the description's mention of filtering 'server side' and keeping queries specific adds pragmatic context. The example year '2025' in the year field description is also helpful.

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 explicitly states the tool searches inside a past monthly kasko list, addressing historical questions like vehicle valuations earlier in the year. The verb 'search' and resource 'archive' are clear, and the purpose is distinguished from siblings by focusing on historical data not available via live endpoints.

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 clearly states when to use this tool: for historical questions that live endpoints cannot answer. It provides an example ('what a vehicle was valued at earlier in the year') and advises to keep queries specific, implying efficient usage. However, it doesn't explicitly exclude other scenarios or mention when not to use it, but the context of eight sibling tools and the open-world hint suggests alternatives exist.

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