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

Annotations already establish readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds valuable behavioral context beyond those annotations: it returns live starting prices in USD, includes image and product URLs, explains the total_count/capped distinction, and notes that metal affects returned prices and URLs. No contradictions with 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 compact and front-loaded: purpose first, then usage context, then return contents, then one caveat about capped counts. Every sentence earns its place without repeating schema details or annotations.

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 9-parameter tool with an output schema present, the description is remarkably complete: it states what is searched, when to use it, what results look like, how to follow up, and the one non-obvious behavioral caveat (capped counts are lower bounds). The output schema handles return shape details, so no additional documentation burden is needed.

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 78%, close to the high-coverage baseline, and the schema already documents key parameters like query, category, metal, and product_line in detail. The tool description adds some semantic context (e.g., metal variants drive the returned price/URL, style code examples), but it doesn't significantly expand parameter understanding beyond the schema's own descriptions.

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 opens with a specific verb ('Search') and defines the exact resource (the 25karats made-to-order catalog) and the scope (wedding bands, engagement rings, sets, fine jewelry). It also clarifies that search is by keywords or style code, and lists the concrete return contents, making it unmistakably distinct from sibling tools like get_product or price_product.

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 gives explicit when-to-use guidance ('Use this first when a shopper describes what they want') and prescribes follow-up tools (get_product for options, price_product for exact pricing). It doesn't explicitly name alternatives to exclude (e.g., search_diamonds for diamonds), but the contextual cues and follow-up pointers provide clear usage direction.

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