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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), but the description goes further by disclosing what the response contains: per-line prices, a total, and a note when a bundle is cheaper. That output-shape disclosure is genuinely useful given there is no output schema.

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 tight sentences with the primary output (prices and total) front-loaded and the conditional bundle behavior following. No filler or redundancy.

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 simple, single-parameter read tool with full schema coverage and safe annotations, this is close to sufficient; it even sketches the return shape. The bundle clause ('it says so') stays vague about how that alternative is surfaced, leaving a small gap.

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% for the single 'slugs' parameter, so the schema already carries the semantics. The description only echoes the parameter as 'a list of dataset slugs' and adds no syntax, count limits, or format detail beyond what is structured.

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 states a concrete verb and resource: it returns line-item prices and a total for a list of dataset slugs. That clearly separates it from buy_dataset and create_checkout, though it never names a sibling explicitly.

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?

There is no stated when-to-use condition or routing to alternatives such as buy_dataset or create_checkout. The pre-purchase framing is inferable from the name and output, but nothing in the text tells the agent when this tool is the right choice versus its siblings.

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