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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavior: the call is free, the full file is only delivered after payment, and the next step is supplying a tier plus billing contact for an invoice. It does not describe behavior on an unknown or ambiguous slug, which keeps it from a 5.

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?

Front-loaded with the verb and identifier, then the return payload, then the commercial mechanics — a sensible order. The content enumeration is dense and reads as one long run-on sentence, but nearly every clause names a distinct returned field rather than padding.

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, the description carries the return-value burden and does so thoroughly, listing the fields the card exposes plus the free-sample and purchase paths. For a single-parameter read tool with full annotation coverage, an agent has everything needed to call it and act on the result.

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 schema already gives an example. The description still adds meaning beyond it: the value may be an exact dataset name as well as a slug, and slugs are obtainable from list_datasets. That name-vs-slug flexibility is not expressed in the schema, so the description earns above baseline.

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 ('One dataset's card by slug') and then enumerates exactly what the card contains: audience, row semantics, headline finding, coverage, as-of date, row count, sources, tiers, page and sample links, purchase path. It also names where the slug comes from (list_datasets), which separates it from that sibling and from get_dataset_sample.

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 clear invocation context ('by slug (from list_datasets) or exact name') and signals the follow-on action ('reply with a tier and a billing contact'). It does not explicitly state when to prefer this over list_datasets or get_dataset_sample, but the parenthetical sourcing and the 'Free' marker make the intended use unambiguous.

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