models

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

No annotations are provided, so the description carries the full burden. It discloses that the tool lists models with pagination (page and total parameters) and returns metadata, which covers basic behavior. However, it lacks details on rate limits, authentication needs, error handling, or what specific metadata is included, which are important for a tool with no annotation support.

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 appropriately sized and front-loaded: it starts with the core purpose, followed by usage advice and parameter details. Every sentence adds value, with no redundant information. It could be slightly more structured (e.g., separating usage notes from parameter descriptions), but it's efficient and clear.

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 moderate complexity (2 parameters, no annotations, no output schema), the description is somewhat complete but has gaps. It explains the purpose, usage, and parameters, but lacks details on return format (beyond 'metadata'), error cases, or how pagination works in practice. Without annotations or output schema, more behavioral context would improve completeness.

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 has 0% description coverage, so the description must compensate. It adds meaning by explaining that 'page' is for pagination (page number) and 'total' is the number of models per page, which clarifies their roles beyond the schema's generic titles. However, it doesn't specify default values, constraints (e.g., min/max), or how null values are handled, leaving some gaps.

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 the tool's purpose: 'List available models on fal.ai.' It specifies the verb ('List') and resource ('available models on fal.ai'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'search' or 'schema', which could also involve models, so it doesn't reach the highest score.

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 provides implied usage guidance: 'Ensure to use the total and page arguments. Avoid listing all the models at once.' This suggests pagination is required and warns against retrieving everything at once. However, it doesn't explicitly state when to use this tool versus alternatives like 'search' or provide clear exclusions, leaving some ambiguity.

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