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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false). The description adds non-obvious behavior beyond that: AND semantics (only datasets containing every column), the inverted-index basis, narrowing via dtype/org, and a hard cap of n ≤ 20. It does restate return fields, which the output schema already provides.

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 routing rule (this tool vs. `search`) is front-loaded and the constraint/return details follow logically. Length is inflated by bilingual duplication of the same content and by listing return fields already in the output schema.

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?

Covers the essential selection logic, match semantics, filter options, and result cap, which is sufficient for a read-only query tool with an output schema and annotations. The only real gap is the undocumented `group` parameter.

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 carry the load, and it mostly does: `names` requires ALL listed columns to match, `dtype`/`org` are narrowing filters, and `n` is capped at 20. The boolean `group` parameter is never mentioned in either place, leaving one gap.

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+resource (find datasets) and the exact scope constraint: ALL given columns present and no topic. It explicitly names the sibling `search(query, fields=...)` for the topic case, so an agent can distinguish the two without opening either 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?

Gives both when-to-use and when-not-to-use in one move: use this when columns are the only condition (query fixed to an empty string), and use `search` instead when a topic exists. The alternative and the condition selecting it are stated explicitly.

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