Find Hugging Face datasets

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

With no annotations, the description must carry the behavioral disclosure burden. It usefully states what results include (revision, card metadata, reconciled paper links) and notes that paper links are conditional ('when available'). However, it does not describe search semantics, result ordering, pagination, or output shape, leaving moderate gaps.

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, focused sentence that places the verb and target resource first, then adds useful qualifiers. No unnecessary words or redundant restatements of the tool name.

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?

For a simple two-parameter search tool, the description covers the core purpose and some result details, but it omits guidance on when to choose this tool over related finders and leaves parameter semantics undocumented. It is adequate but not fully self-sufficient.

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 compensate for the lack of parameter documentation. It does not explain what 'query' should contain or how 'limit' affects results. While the parameter names are somewhat self-explanatory, the description adds no specific meaning beyond 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 names a specific verb ('Find'), a specific resource ('dataset repositories on Hugging Face'), and adds distinctive result details ('revision, card metadata, and reconciled paper links'). This clearly distinguishes it from sibling tools like find_models and find_implementations.

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 usage for searching Hugging Face dataset repositories, but it does not explicitly state when to use this tool over alternatives such as find_models or search_papers. No exclusions or selection criteria are provided.

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