ML Model Details

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

Annotations declare readOnlyHint=true and destructiveHint=false, so the description is not required to reiterate safety. It adds value by listing the types of metadata returned (downloads, likes, tags, etc.), which goes beyond the 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?

Two sentences: first states purpose and content, second gives usage guidance. Every sentence is necessary, front-loaded, and concise with no redundancy.

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 is simple (one required parameter, read-only, with an output schema), the description covers the purpose, input source, and example format. It is sufficient for an agent to correctly invoke the tool.

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 schema already documents model_id with a description and example. The description echoes the same guidance ('Use model_id from hf.models search (e.g. ...)'), adding no new semantic meaning beyond what the schema provides. Schema coverage is 100%.

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 'Get full metadata for a HuggingFace model' specifying the verb 'get' and the resource 'full metadata'. It lists specific attributes (downloads, likes, tags, etc.), distinguishing it from sibling tools like hf.hub.models which is for search.

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 explicit guidance on the input source: 'Use model_id from hf.models search' with an example format. It implies this tool is for fetching details after search but does not explicitly state when not to use it or alternatives.

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