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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuine value beyond them by disclosing the return contents (schema, coverage, field definitions) and the not_found error for an unknown id — useful pre-call knowledge. It stops short of noting auth or rate-limit behavior.

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, zero filler, with the payoff (what is returned) front-loaded and the failure mode relegated to sentence two. Nothing to cut.

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?

For a single-parameter read tool with no output schema, the description covers both the return shape and the error case, which is enough to call it correctly. It would be complete at a 5 if it sourced the dataset id (e.g. from search_datasets).

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 the single parameter's schema text ('Dataset id.') matches what the description implies. The description adds nothing about id format, case sensitivity, or where such an id comes from, so the baseline 3 is correct.

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 (returns) and resource (schema, coverage and field definitions of one dataset), so an agent knows exactly what it gets back. It does not name or differentiate itself from the obvious sibling search_datasets, which is the only thing keeping it from a 5.

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?

Usage is only implied: the 'one dataset id' framing suggests it follows a search, but the description never says when to call this versus search_datasets, nor what to do if the id is unknown beyond the error. No exclusions or alternatives are stated.

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