get_product

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

With no annotations, the description carries full transparency burden. It reveals input flexibility (accepts both canonical and retailer IDs), return content (technical specs, pricing, offers), and no side effects. Could be slightly improved by noting response structure or limitations, but overall sufficient for a read-only tool.

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?

Concise at three sentences, front-loaded with main purpose. The enumerated return types are helpful but could be tightened. No wasted words.

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 simplicity (one parameter, no output schema), the description fully covers purpose, usage, input variants, and output content. No gaps remain for effective tool selection and invocation.

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 describes product_id as 'The unique product ID'. The description adds critical detail: 'Accepts both canonical product IDs and original retailer offer IDs', which significantly clarifies acceptable inputs 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 tool's function: 'Get full details for a single product by ID'. It enumerates the types of data returned (specs, pricing, stock, offers) and distinguishes from sibling search_products by indicating it is used for detailed retrieval after search.

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 provides usage context: 'Use this after search_products to get detailed specs for comparison or recommendations' and 'Always call this when a user needs precise product attributes'. This gives clear guidance on when and why to invoke the tool.

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