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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the description only needs to add context. It does add real value: house default appears first, entries carry sizes, ratios, lengths and accepted inputs, and prices surface on get_task cards rather than here. It stops short of describing ordering guarantees beyond 'default first' or how many entries come back.

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 clause carries information and the purpose is front-loaded, so there is little waste. However the telegraphic style ('house default first, with sizes, ratios, lengths and what each takes') is hard to parse on first read and a couple of clauses need re-reading to decode.

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 read tool with no output schema, the description covers the essential ground: what is listed, per-kind differences, ordering by house default, and where pricing lives instead. It does not describe the shape of a returned model entry, but that is a minor gap given the tool's simplicity.

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 0%, so the description must carry the meaning of the single enum, and it largely does: it explains what image, video and sound return (default first, sizes, ratios, lengths, accepted inputs) and what writer returns (models nameable by another_ai on reply). All four enum values are addressed, though the wording is compressed and 'what each takes' is left vague.

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?

Opens with a specific statement of the resource: 'The models this user can use,' scoped to the calling user. It then distinguishes what the kind values return (image/video/sound vs writer), so an agent can tell it apart from siblings like get_task or get_credits. The phrasing is fragmentary, which costs a point against a fully crisp verb+resource statement.

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 rather than stated: 'A task uses the default unless the brief or reply names one' tells the agent it only needs this list to name a non-default model, and the writer clause ties that kind to another_ai on reply. There is no explicit 'use this when' framing or named exclusion against alternatives such as get_task, so the agent must infer the trigger.

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