list_models

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

No annotations are provided, so the description carries the transparency burden. The verb 'List' implies a read-only operation and the phrase 'all available' discloses scope. However, it does not explicitly state non-modification, pagination, or any authentication requirements, leaving some behavioral context implicit.

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 a single, front-loaded sentence with no redundant words. Every word contributes to conveying the action and resource, achieving maximum conciseness.

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 simple list tool with one optional parameter and no output schema, the description adequately conveys the core purpose and scope. It omits mention of the platform filter (though the schema covers it) and does not describe the return format, but these are minor gaps 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?

The input schema fully describes the optional 'platform' parameter with examples and 100% coverage. The description itself does not mention the filter or add any meaning beyond the schema, so the baseline score 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?

The description clearly identifies a list operation for all AI models/platforms in DreamingAI, using the specific verb 'List' and resource 'available AI models and platforms'. It distinguishes itself from siblings like 'get_model' (single model retrieval) and 'switch_model' (changing active model) by emphasizing 'all available'.

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 implies usage (use when you need to see all models/platforms) but provides no explicit guidance on when to use this tool versus alternatives like get_model or switch_model. No exclusions or alternative recommendations are mentioned.

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