Search Models

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

Annotations are minimal (only title), so the description carries the full burden. It discloses no behavioral traits beyond 'search'—nothing about result ordering, pagination, authentication, or filtering behavior. This is a significant gap for a tool with no annotation hints.

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 short sentence, making it concise and front-loaded. However, it is under-specified, lacking any context that would make the sentence more informative. It earns a middle score for brevity without sacrificing clarity, but fails to pack useful content.

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?

Despite a rich input schema and an output schema (per context signals), the description is too sparse to be complete. It does not mention how the search behaves (e.g., fuzzy matching, defaults, result limits), which would be valuable for an agent deciding whether to invoke it. The schema covers parameter semantics, but the description adds no contextual value.

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 100%, so the baseline is 3. The description adds no parameter-level details, but the schema itself documents all five parameters with clear descriptions. The description does not compensate or enhance beyond the schema, so a baseline score is appropriate.

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 it searches for models on ModelScope, using a specific verb and resource. It distinguishes from sibling tools like search_datasets and search_papers by explicitly naming 'models', which is helpful for selection.

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?

No guidance is provided on when to use this tool versus alternatives, nor any context about prerequisites or exclusions. The description simply states the action without situational cues, leaving the agent to infer usage from the tool name alone.

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