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

Annotations already cover readOnly/idempotent/openWorld, and the description goes well beyond them: caching up to 1 hour, charge/no-charge rules for no-match vs errors, latency range, price and free-tier limits per IP per UTC day. It also flags returned text as untrusted data, which is genuine behavioral context an agent needs before consuming output.

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?

Purpose and scope are front-loaded in the first clause, and most sentences carry operational value (cost, caching, latency). However, it is a dense run-on built from semicolon fragments, and the warning about 'on-chain strings' looks copied from a crypto tool and is irrelevant to a dataset search.

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?

With an output schema present, the description need not explain return shapes, and it nonetheless lists the key returned fields plus ranking. Cost, caching, rate limits and untrusted-content handling round out everything an agent needs before calling a 6-parameter paid search 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?

Schema coverage is 100% and each parameter carries its own description (size buckets, task tags, licence tag caveat), so the schema does the heavy lifting. The description only enumerates which filters exist and notes the licence caveat already present in the schema, adding marginal meaning. Baseline 3 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?

States a specific verb (find) and resource (datasets) and pins the scope hard: 'Hugging Face Hub only,' repeated for emphasis. It also declares ranking (by downloads) and return fields, so an agent can distinguish it from generic search siblings like web_search or search_papers without opening a schema.

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 'Hugging Face Hub only' constraint is stated twice, which effectively tells the agent when NOT to use it (any non-Hugging Face dataset need). It also says filters are optional, clarifying the required query is the only mandatory input. It stops short of naming an alternative tool for out-of-scope dataset searches.

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