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 genuinely new context: the payload is unredacted (full fields, exact prices) and identical to the public sample CSV, telling the agent it is a fixed, non-parameterized preview rather than a truncated query result.

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?

A single sentence, front-loaded with the resource and its scope, with zero filler. Every clause (row count, full fields, exact prices, CSV equivalence) carries information.

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 does its job by stating the return content: 10 rows, full fields, exact prices. What it omits is any pointer on how to get more than the sample, which would help an agent decide the next step, but nothing needed to invoke the tool correctly is missing.

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?

The tool takes zero parameters, which is the baseline-4 case. The description is consistent with that — it makes clear the result is a fixed set with no filtering or paging knobs to supply.

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 names the exact resource and its scope: the 10 free sample rows of the RateCard Health database, with full fields and exact prices. An agent knows precisely what it gets back. It does not explicitly contrast with siblings like search_publications or get_publication, so it stops short of 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 'free sample' framing suggests previewing the dataset before a fuller query, but the description never says when to use this instead of search_publications or get_price_index. No exclusions or prerequisites are stated.

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