Dataset Search Hf

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

Annotations only declare readOnlyHint=true, so the description carries the burden of behavioral disclosure. It mentions the search is over public datasets and returns repo IDs and SHAs, but says nothing about pagination, result caps, or sorting behavior beyond 'popularity' when the schema allows likes/downloads/recent.

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?

A single efficient sentence, front-loaded with the verb and resource. No waste, though it is arguably under-specified rather than merely concise.

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?

An output schema exists so return values need not be explained, but the nested request object has 5 undocumented parameters and there are no annotations covering behavior beyond readOnly. For a search tool with 5 filter parameters, the description is too thin.

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% at the top level, and the nested request object's fields (sort, tags, limit, query, author) are mostly undocumented. The description only hints at popularity sorting and return fields, not compensating for the coverage gap on tags, limit, or author.

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?

States a specific verb (Search) and resource (public Hugging Face datasets) with scope 'by popularity'. Distinguishes from sibling dataset_fetch_hf/dataset_probe_hf to a degree, though it doesn't name them explicitly to route the agent.

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 when-to-use or when-not-to-use guidance. Nothing tells the agent how this differs from dataset_fetch_hf or dataset_probe_hf, which appear adjacent in the sibling list.

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