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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety needs no restating. The description adds genuinely useful behavior beyond them: the schema exposes exact text-dimension values that are case-sensitive and must be pasted verbatim into SQL filters — a real gotcha an agent would otherwise hit.

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?

Two sentences, front-loaded with what is returned, then the workflow constraint. The parenthetical about case sensitivity is dense but earns its place; the enumeration of returned fields is slightly list-heavy but not wasteful.

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?

The tool is simple — one required parameter and an output schema that already documents the return shape — and the description still covers content, a case-sensitivity caveat, and its place in the query workflow. Nothing an agent needs in order to call it correctly is missing.

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?

There is a single parameter with 100% schema description coverage, and the schema already ties it to `list_datasets` with an example. The description adds nothing about the `table` argument, so the schema-only baseline of 3 applies.

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 resource (a dataset's schema) and enumerates its contents: description, primary key, typed columns with meaning, exact text-dimension values, and sample rows. An agent can distinguish it from list_datasets (catalog listing) and query_sql (execution) without opening any 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?

It gives an explicit ordering rule: call this before writing `query_sql`. The alternative it gates is named directly, so the agent knows both the trigger and the downstream tool it feeds.

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