chewy_gtin_lookup

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

With no annotations, the description carries the full burden, and it does well: it discloses the batch limit (up to 20), the single-call behavior, and the crucial partial-failure semantics (unrecognized barcodes go to not_found instead of failing the whole call). It also names the response fields. It does not mention rate limits or authentication, but for a simple lookup, the key behaviors are 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?

Every sentence earns its place: purpose, batch capability, input format with example, partial-failure behavior, and downstream usage. It is front-loaded with the main action and contains no filler, jargon, or redundancy. Despite covering multiple aspects, it remains compact and scannable.

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 single-parameter lookup tool with no output schema, the description is nearly complete. It explains the input format, limits, error behavior, and what to do with the results. It names the output fields (part_numbers, not_found), but does not specify their types or the overall response shape. Given the tool's simplicity, this is a minor gap rather than a blocking omission.

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 100%, so the schema already documents gtins as 'Comma-separated GTIN/UPC barcodes, up to 20.' The description adds value beyond the schema by providing a concrete example ('192268541316') and explaining how unrecognized barcodes are handled in terms of output fields. That is meaningful semantic enrichment, not mere repetition.

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 and resource: 'Resolve Chewy GTIN/UPC barcodes to part numbers.' It clearly distinguishes this tool from Chewy siblings by focusing on the barcode-to-part-number mapping, and explicitly frames its output as feeding into chewy_product/chewy_products. An agent can immediately understand what this tool does and how it differs from chewy_search or chewy_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 provides clear context: it handles batch lookup up to 20 barcodes, and the resulting part_numbers are meant to feed chewy_product/chewy_products. This implies when to use it (when barcodes are available and part numbers are needed). It does not explicitly name alternatives or exclusions, but the purpose statement and sibling set make the appropriate use case evident.

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