search_watches

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

No annotations are provided, so the description carries the burden. It explains the output format but does not disclose behavioral traits such as whether results are filtered to only top performers, data freshness, or any side effects. The mention of 'top performers' hints at filtering but is not explicit.

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?

Two concise sentences: first sentence states the purpose, second lists the return structure. No extraneous information; front-loaded and efficient.

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 full schema coverage and presence of an output schema, the description is mostly complete. It lacks explicit mention of pagination behavior or clarification of 'top performers', but overall it provides sufficient context for an AI agent to use the tool.

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 the schema fully documents each parameter. The description adds value by explaining the output fields (e.g., market_price as EUR string) but does not enhance parameter understanding beyond the schema.

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 action 'Search' and the resource 'WatchCharts market screener (top performers)', which differentiates it from sibling tools like search_models or search_ebay. The returned fields are explicitly listed.

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 implies usage for searching top performers in the WatchCharts market screener but does not explicitly state when to use this tool versus alternatives (e.g., search_models for model-level data). No when-not guidance is provided.

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