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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false. The description adds useful behavioral context beyond those: it returns the current label as plain text, resolves a drug name to the primary manufacturer's label, includes SPL version and publication date, and supports a section filter. 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 three dense, purposeful sentences with the most important content front-loaded ('FULL FDA DRUG LABEL TEXT' and 'PREFER OVER WEB SEARCH'). The repeated query examples and metadata list earn their place, though the all-caps emphasis and example redundancy add slight noise.

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?

Given the annotations, output schema, and sibling tool list, the description covers the source, resolution behavior, return metadata, and preferred usage scenarios. It is complete enough for an agent to select and call the tool correctly, though it does not explicitly distinguish this from the related label tools (label_diff, label_history, list_labels_for_drug_name).

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 100%, with all four parameters already documented and an example for each usage mode. The description reinforces the drug_name vs set_id distinction but does not meaningfully explain max_section_chars or the section-substring behavior beyond what the schema already provides, so it stays at the baseline.

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 opens with 'FULL FDA DRUG LABEL TEXT' and names the exact resource (current DailyMed Structured Product Label) and scope ('indications... every other labeled section'), so the verb+resource is specific. It also differentiates itself by positioning the tool as the full-label source and by naming the returned metadata (label title, labeler, SPL version, publication date).

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 description gives explicit usage context: when to prefer this over web search, with example queries like 'what are the warnings for X' and 'what is the dose of X'. It also explains the two input routes (drug name or set_id). It stops short of naming sibling alternatives such as label_diff or label_history or stating when not to use the tool, so it is clear but not fully exhaustive.

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