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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so safety is covered. The description adds concrete behavior beyond that: the exact return structure, pagination semantics (next_cursor, null meaning), the critical clarification that publisher is the account that published here (not the original data source), and that omitting query lists recent datasets. It does not mention rate limits or potential performance, but for a read-only search that's acceptable.

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 description is concise yet information-dense, covering purpose, usage, examples, return format, pagination, and follow-up steps in three sentences. It is front-loaded with the action and example, then fills in edge cases and clarifications. Every sentence earns its place; no fluff.

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 there is no output schema, the description must detail return values, which it does thoroughly (datasets array with fields, next_cursor). It also addresses pagination, the distinction between publisher and source, and follow-up actions. The tool is simple enough that the description covers all needed aspects for an agent to call it correctly.

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 provides parameter names but no descriptions (coverage 0%), so the description carries the full burden. It explains `query` with an example, `limit` (implied by example but not explicit max, though schema gives that), `cursor` for pagination and how to use it (pass next_cursor back as cursor), and the effect of omitting `query`. It also clarifies that `topic` is available but not described; however, the core parameters are well explained. The description adds significant meaning beyond 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 states it performs 'Full-text search over every public dataset on Mostly Right', which is specific about the verb and resource. It distinguishes itself from the sibling `search` (likely a general search) by its scope and from `get_dataset` by its search-and-list nature. The example invocation makes the purpose immediately concrete.

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?

It explicitly says to 'Follow up with get_dataset(slug) for tables and schemas', which guides the agent to the next logical step. It also explains when to omit the query ('to list the most recently published datasets'), and the presence of siblings like `search` implies differentiation. The no-account-needed statement clarifies prerequisites.

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