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

Annotations cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the description's remaining job is behavioral context, and it delivers: the 20 MiB size limit, that unclear values stay empty with an issue, that Shopify and Google output is validated against platform feed rules, and that the result includes summary, mapping, issues and CSV text. Not exhaustive on auth or failure modes, but well beyond the 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?

Front-loaded with the conversion action and its output targets, and each subsequent sentence adds distinct information (input formats, normalization behaviors, validation, return contents) with no filler. It is long but dense rather than padded.

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 complex 8-parameter tool with nested objects and an output schema, the description covers inputs, targets, limits, transformation behavior and error handling. Since a return-value schema exists, the brief mention of the return payload is sufficient and nothing critical is missing.

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 100%, so all eight parameters (including the file object and the options blob) are already documented in the schema, including the target enum values and the NormalizeOptions pointer. The description adds only the source-format list and the notion of derived/default/missing columns, so the baseline of 3 applies.

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?

States a concrete verb (converts) and resource (a product table/supplier list, ERP or shop export) plus all four supported output targets. An agent can distinguish this from merchant_validate and supplier_compare purely from the description, since this one builds an import file rather than validating or comparing.

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 makes the input formats (CSV, TSV, XLSX up to 20 MiB) and output targets explicit, which gives strong implied context for when to pick this tool. However, it never names or contrasts the sibling tools (merchant_validate, supplier_compare, documents_tables) or states when NOT to use it, so routing still requires inference.

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