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

Annotations already cover read-only and non-destructive behavior, but the description adds substantial payment and settlement semantics: pricing is per row in USDC via x402, settlement happens only after rows are produced, failed calls cost nothing, and the limit is capped at 100 rows. These are the critical behavioral details an agent cannot infer from the annotations.

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 core purpose is front-loaded in the first sentence, and the remaining sentences carry useful pricing and workflow context. It is slightly dense but no sentence is wasted, so it reads as appropriately sized rather than bloated.

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 complex paid query tool with no output schema and partial schema coverage, the description covers the essential workflow: filtering semantics, payment timing, quote retrieval, row-limit pricing, and the threshold at which file purchase is preferred. An agent has enough information to call it correctly and understand the cost consequences.

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?

With only 33% schema description coverage, the description compensates by explaining that state, city, county, and zip are exact-match filters and that only the columns present in the dataset apply. It also clarifies that payment scales with the requested limit, though it does not fully document every parameter beyond that.

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: return matching rows from one dataset filtered on exact column values. It names the filterable columns and explicitly notes they are dataset-dependent, which lets an agent distinguish it from sibling tools like buy_dataset and search_datasets.

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 when-to-use guidance, including calling without a payment header first for an exact quote, and a when-not-to-use condition: datasets under 5,000 records must be bought outright instead. This routes the agent away from per-row querying in the wrong scenario.

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