list_models

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

No annotations are present, so the description carries the full burden. It discloses default behavior (include_unprobed=True) and parameter constraints but omits details like read-only nature, pagination, or potential costs. For a simple list tool, this is adequate but not thorough.

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 concise with a front-loaded purpose sentence and organized Args list. Every sentence adds value, though minor improvements like separating purpose from args could enhance structure.

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 the tool's simplicity (4 optional params, output schema exists), the description covers purpose and all parameters. It doesn't discuss sorting or rate limits, but these are non-essential for a basic list operation.

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?

With 0% schema coverage, the description fully compensates by explaining each parameter's purpose and format (e.g., capability as list of tags, min_context_length in tokens). This adds meaning beyond the schema's type and default values.

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 states 'List models matching the filters' with a specific verb ('list') and resource ('models'). It distinguishes itself from sibling tools like add_models (write) and invoke_model (invocation) as a read-only listing operation.

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 through filter parameters but does not explicitly specify when to use this tool instead of siblings like model_performance or usage_guide. No when-not or alternative guidance is provided.

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