find_similar_models

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

With no annotations, the description carries the full burden of disclosing behavioral traits. It explains the core behavior (finding and filtering alternatives) but does not mention any potential side effects, auth requirements, or rate limits, nor does it note that it is a read-only operation. This is adequate for a simple retrieval tool but lacks extra contextual disclosure.

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 efficient: a one-sentence purpose statement followed by an Args list. Every word contributes, and the most important info (purpose) is front-loaded. There is no repetition of schema fields that are self-explanatory for types alone.

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 only 3 parameters, a clear purpose, and the existence of an output schema that likely documents return structure, the description fully covers what an agent needs to call the tool correctly. It explains each parameter and the filtering logic, leaving no gaps beyond what the output schema would cover.

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 description coverage is 0%, so the description must fully compensate. It does: each parameter gets a concise but meaningful explanation—model_id as the HF repo id, variant with the three enum values and what they mean, and limit with the allowed range (1-20). This adds substantial value over the raw 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?

The description opens with a specific verb ('Find') and a precise scope: alternative models for the same task as the given model, filtered by relative size. It clearly distinguishes this from sibling tools like search_models (general search) and compare_models (comparison) by emphasizing same-task and size filtering.

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 when to use it (when you need alternatives for a specific model, filtered by size) through its purpose statement, but it does not explicitly mention sibling alternatives or when-not conditions. It gives clear context without exclusions, so a score of 4 is warranted.

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