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

Annotations already cover read-only, idempotent, open-world and non-destructive, so the bar is lower; the description still adds real value by disclosing accepted input formats, the exact required-field ruleset, and the shape of the result (% SKUs OK, issue counts, sample issues). It does not cover failure modes (unreachable URL, oversized feed) or how many sample issues are returned, which keeps it below a 5.

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?

Two sentences, front-loaded with the action, and the parenthetical field list is compact rather than padded. The required-fields enumeration is long but it is the substance of the check, so it earns its place; minor density cost only.

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?

With no output schema, describing the return payload is essential and the description does it. Annotations carry the safety profile and the schema carries parameter docs, so the only gaps are error behavior and result limits — useful but not blocking for a correct call.

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% with only two parameters, so the baseline is 3. The description usefully implies the accepted feed formats behind feed_url (XML RSS/Atom, CSV, TSV, JSONL), but seller_name is never mentioned, so no meaning is added for that parameter.

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 specific verb pair ('fetches... and checks') and a concrete resource ('public product feed'), then names the exact spec being validated against (OpenAI Commerce products feed spec). The ChatGPT/OpenAI framing cleanly separates it from the sibling validate_feed_for_google without needing the name alone.

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?

Usage is implied by the spec name — an agent can infer this is the ChatGPT-side validator — but there is no explicit when-to-use statement, no mention of when to prefer validate_feed_for_google or draft_supplemental_feed, and no prerequisites. It falls to inference rather than guidance.

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