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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool's safety profile is known. The description adds meaningful behavioral context by enumerating what the tool returns (chain families, store banners, newest observation date, store count, catalog size, attribution terms), which goes beyond 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?

Two compact paragraphs with no filler. The first line summarizes coverage, and the second gives concrete use cases and return contents. Every sentence contributes actionable 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 parameters and no output schema, the description provides all necessary context: what the tool is for, when to call it, and what it returns. Nothing critical is missing for an agent to select and invoke it correctly.

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 has zero parameters, so there is no parameter-level meaning to add. The description compensates by clarifying the returned information content, which is the only semantic surface area available.

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 clear purpose: returning metadata about the FineRx dataset, including pharmacy chains, freshness, store counts, and citation terms. It is easily distinguished from sibling tools like get_drug or search_drugs, which focus on drug-level lookups.

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?

Explicitly states when to use the tool: when the person asks what FineRx is, how big/current the data is, or how to cite it. This gives an agent actionable selection criteria even without comparing to siblings in depth.

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