list_models

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses that results are 'live from the API,' that a default is marked, and that ID suffixes encode whether an image input is required. These are useful operational details beyond the schema.

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?

The description is two compact sentences with the core purpose front-loaded and the model ID convention provided as useful secondary context. Every sentence adds value and there is no filler or repetition of schema 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?

For a zero-argument listing tool with an output schema, the description adequately covers purpose, freshness, default marking, and ID semantics. It lacks an explicit connection to when to use it alongside the generation siblings, but the overall context is sufficient for correct invocation.

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?

There are zero parameters, so schema coverage is effectively 100% and the description has no parameter burden. The baseline for a zero-parameter tool is 4, and the description appropriately focuses on output behavior rather than arguments.

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 uses a specific verb and resource: 'List Siray's active image models.' It clearly identifies a read-only catalog operation and distinguishes itself from the generate_* siblings by describing an informational listing rather than an image-generation action.

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 usage is implied: an agent would call this tool when it needs to discover available model IDs or check the active/default model. However, the description does not explicitly say when to prefer list_models over generate_image or generate_backdrop, nor does it describe a discovery-before-generation workflow.

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