ML Model Details

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true. The description adds value by enumerating the metadata fields returned (downloads, likes, tags, etc.), which helps the agent understand the output beyond the schema. No contradictions with annotations.

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 two sentences with no wasted text. The first front-loaded sentence states the purpose and key details, and the second provides actionable guidance. Every sentence is essential 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 simplicity (single parameter, rich annotations, and presence of an output schema), the description covers all necessary context: what the tool does, the required input, and how to obtain it. No gaps are apparent for an agent to use it correctly.

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 100% with a descriptive parameter definition. The description adds further meaning by specifying the source ('Use model_id from hf.models search') and providing an example format, which aids in selecting the correct parameter value. Baseline 3 is exceeded due to this added context.

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 verb 'Get' and the resource 'full metadata for a HuggingFace model', listing specific metadata fields (downloads, likes, tags, etc.). It differentiates from sibling tools like 'hf.hub.models' by referencing the model_id from that search, making its role distinct.

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 explicitly says 'Use model_id from hf.models search', providing a clear prerequisite and sequential context. It implicitly advises against using this tool without a model_id, though it does not explicitly list when-not-to-use or alternative tools for other purposes.

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