list_models

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

No annotations provided, so description must disclose behavior. It describes the return format (dict with count and list of models) but omits details like read-only nature, rate limits, or authorization requirements. Adequate for a simple list tool but lacks full transparency.

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?

Compact docstring format with Args and Returns sections. Every sentence adds value, no fluff. Front-loaded with main purpose.

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?

Given no output schema, description provides return type and fields. Covers all 3 parameters with examples. Missing mention of pagination, sorting, or default max results, but overall sufficient for a listing tool.

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 0%, but description compensates fully: explains each parameter with examples (e.g., filter_origin: 'fr', 'us', 'cn'; max_params_b: 'e.g. 32 for ≤32B models'). Adds meaning well beyond the bare 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?

Clearly states 'List open-weights LLMs from quelllm.fr catalog (190+ models).' Uses specific verb 'List' and resource 'open-weights LLMs', distinguishes from siblings like get_model (single) and search_models (search).

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?

Provides context for listing with optional filters, but does not explicitly state when to use versus alternatives (e.g., search_models for full-text search). Still, the purpose is clear for basic listing tasks.

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