get_claims

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

With no annotations provided, the description carries the full responsibility for behavioral disclosure. It explicitly states the operation is read-only and discloses that customer names are not included in the response, which adds valuable context. It also explains the returned summary fields. While it doesn't discuss error handling or pagination behavior, the key non-obvious facts (read-only, omitted field) are covered.

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 extremely concise, using only a few sentences. It front-loads the purpose and read-only flag, then lists the arguments and return fields. Every sentence adds value, with no filler or repetition. The structure is clean, separating arguments from return information clearly.

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 that an output schema exists (per context signals), the description doesn't need to enumerate every return field. It however outlines the key fields (claim id, orderNumber, claimDate, statuses) and explicitly notes the omission of customer names, which is a notable completeness element. It does not mention pagination behavior like total counts or link headers, but for a simple list tool with two params this is acceptable. Overall, it provides enough for an agent to call correctly.

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 input schema has 0% description coverage, so the description must compensate. It clearly explains both parameters: page is zero-based and size is items per page. This adds semantic meaning beyond the bare type and default in the schema, providing clarity that prevents off-by-one errors. The description fully compensates for the missing schema documentation.

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 with a specific verb ('List') and resource ('returns/claims'), and explicitly notes it is for the store and read-only. It is distinguishable from siblings like get_products and get_orders because it focuses on claims, and the first line gives a precise scope.

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 its use case by mentioning 'returns/claims' and the data it returns, but it does not explicitly state when to use this tool versus alternatives (e.g., 'use this for claim statuses rather than orders') or provide exclusion conditions. The context makes it obvious for a human, but an AI agent would benefit from explicit routing guidance.

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