List Chutes media models

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and openWorld, so the safety profile is fully covered. The description adds the useful discovery-role context, but says nothing about result volume, default page size, ordering, or what happens when limit is omitted — the practical behaviors an agent still needs to guess at.

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, zero padding, with the capability statement front-loaded and the routing advice second. Every clause carries information.

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?

An output schema exists, so return values need no explanation, and the sibling workflow is spelled out. The only gap is pagination/default-limit behavior, which matters for a list tool with a 200-item cap but is not covered anywhere in the description.

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 only 33%, so the description must carry weight, and it does: it explains that kind narrows to the four media types and that query is a free-text filter applied to discovery. Only limit is left unaddressed, though its bounds are self-documenting in the schema.

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 (List) and resource (Chutes media-generation models), and enumerates the domains covered (image / video / music / speech). It is immediately distinguishable from describe_media_model, which it names as a separate, narrower step.

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?

Gives an explicit workflow: discover a model here, then call describe_media_model, then generate_media. This tells the agent both when to use this tool and which sibling to reach for next, leaving nothing to inference.

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