get_product

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

With no annotations, the description carries the full burden and does well: it discloses case-insensitive substring matching, optional filters, and the multi-document selection rule (newest general conditions returned, others listed under `other_documents`). It stops short of describing error/not-found behavior, but the core is transparent.

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 roughly 150 words, front-loaded with the primary purpose, and every sentence adds value: output format, matching rule, filter semantics, and edge-case handling. It uses concrete examples like `'2026'` and document type values without redundancy.

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 5-parameter tool with no annotations and an existing output schema (per context signals), the description covers the key behaviors, filters, and the `other_documents` edge case. It lacks explicit handling for no-match scenarios and doesn't clarify `country`/`insurer_slug`, but overall it is sufficient for a competent agent to invoke it 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?

Schema coverage is 0%, so the description must compensate. It explains `product_name` matching (case-insensitive substring), enumerates `document_type` allowed values, and gives an `edition` example with substring semantics. However, `country` and `insurer_slug` are not elaborated, though their roles are inferable from field names.

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 ('Return') and resource ('a product's structured data ... as JSON'), clearly distinguishing it from sibling tools focused on branches, coverages, or general search. It also mentions `source_url` and the `other_documents` field, which further clarifies 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 usage by explaining the matching and filtering behavior, but it does not explicitly state when to choose this tool over alternatives like `search` or `compare_products`. There are no exclusions or alternative-naming mentions, so the guidance remains implicit.

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