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

Annotations cover safety (readOnly) and openness, but the description adds material behavior beyond them: results are label text only, the response includes label set ID and effective date, absence of a match is not evidence of absence, and each successful call costs $0.002 USDC via x402 with failures uncharged. That payment/charging detail is exactly the kind of operational context annotations do not carry; only the label jurisdiction (US openFDA only) is left implicit.

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?

Front-loads the core purpose in the opening clause, then layers the no-severity caveat, the false-negative warning, and pricing. Dense but every clause carries information; the pricing sentence is long but operationally necessary.

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?

An output schema exists, so return-value structure need not be spelled out, yet the description still flags the key fields and the main interpretive pitfall. For a two-parameter read tool this is close to complete, with the only real gap being no note on label coverage (US-only, current vs. historical labels).

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% and already defines both fields, including that 'with' is looked for inside drug A's label. The description reinforces the directional A-label/B-mention relationship but adds no format, normalization, or naming-convention guidance beyond the schema's 'generic name, letters and spaces' rules.

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: matching sentences from the drug interactions section of drug A's FDA (openFDA) label that mention drug B. It also scopes the output (label set ID and effective date) and explicitly rules out what it is not ('no severity score'), which separates it from adverse-event or severity-oriented siblings.

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 a clear usage context and an important interpretation rule: a no-match result does not mean no interaction exists. It does not name an alternative sibling (e.g., FAERS adverse events or a label-summary tool) for when this narrow sentence-matching search is the wrong choice, so it stops short of full when/when-not routing.

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