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

Annotations already declare readOnly, idempotent and non-destructive, so safety is covered. The description adds real context beyond that: results are scoped to one project, tag output is names-only without full value tables, and tags are team-shared, which is non-obvious behavior an agent would otherwise miss.

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 result contents are front-loaded in the first clause, so an agent knows what it gets before anything else. The second sentence about tag reuse is slightly tangential to listing, but it is short and useful for the follow-on tagging workflow.

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 no output schema and a single simple parameter, the description carries the needed burden by naming the returned fields and clarifying that tag values are omitted. Reading it, an agent can call this correctly without further guessing.

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 one required parameter, projectId, with 0% schema description coverage and no explanation in the description. The name is largely self-explanatory and the project scope is implied by 'in a project', but no format, source, or defaulting guidance is provided.

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 and resource ('List the datasets in a project') and enumerates what comes back (id, name, row/column counts, tag names), which implicitly separates it from get_dataset. It stops short of naming get_dataset as the sibling that returns full data, so the differentiation is inferred rather than stated.

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 phrase 'without the full value table' implies get_dataset is the right tool when full data is needed, but the alternative is never named and no explicit when-to-use statement is given. The tagging advice ('reuse a name the list tools already report') is an implied workflow cue rather than a usage rule for this tool.

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