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

Annotations already establish read-only, open-world, and idempotent behavior. The description adds valuable behavioral context: one entry per ATC code, single-ingredient versus combination mapping differences, and that data comes from NLM RxClass. There is no contradiction with 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?

The description is well-structured and front-loaded with a clear one-sentence definition, followed by actionable bullets and a concise return-behavior note. Every section earns its place without redundancy or filler.

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 single-parameter read-only tool with an output schema and rich annotations, this description is complete. It covers what the tool does, example usage, return cardinality, multi-code behavior, and data source. Nothing critical is missing for correct invocation.

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 input schema already fully documents the single parameter with brand/generic details and an example, so description-level parameter explanation adds limited value. The metformin-to-A10BA02 example reinforces the parameter but does not materially expand semantic understanding.

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 the tool looks up WHO ATC classifications for a drug by name and provides a concrete example. However, it does not explicitly distinguish itself from sibling atc_lookup, leaving some potential ambiguity for an agent choosing between similar-sounding tools.

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?

The bullet list gives clear, actionable scenarios for when to use the tool: finding ATC codes, identifying class hierarchy, and cross-referencing drugs. It does not explicitly state when not to use it or name alternatives, but the guidance is specific enough for most selection contexts.

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