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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds useful context: source (FDA labels), cost ($0.10), and cryptographic attestation. But it does not disclose return format, pagination, or limitations, so the added value is moderate.

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 description is front-loaded with purpose and outputs, followed by use cases and cost/verification details. Each sentence adds some value, though the attestation note could be trimmed for an AI agent.

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 1-parameter read-only lookup, the description covers the key return fields, source, cost, and verification. It lacks any mention of drug_name format, but overall is reasonably complete given the lack of an output schema and low parameter complexity.

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 description coverage is 0% for the single parameter drug_name, and the description does not elaborate on its expected format (e.g., brand vs generic, case sensitivity). The param name and tool context imply it's a drug name, but the description fails to compensate for the missing schema detail.

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 clearly states it returns FDA drug label intelligence with specific fields (brand/generic names, manufacturer, route, indications, warnings). It distinguishes this from sibling tools like get_drug_adverse_events by focusing on label content, though it doesn't explicitly name alternatives.

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?

It provides explicit use cases: formulary review, pharmacology research, and adverse event context. However, it lacks exclusions or alternative tool suggestions, so it doesn't fully meet the 'when not to use' bar.

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