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

With no annotations provided, the description carries the full burden. It mentions the data source (public CMS provider-level data) and pricing, but does not disclose output format, pagination behavior, or error handling. It adds some context but leaves gaps in behavioral traits.

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 concise at about 75 words, front-loads the main purpose, and every sentence adds value (purpose, example, filters, data source, price). No redundancy or unnecessary detail.

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 7 parameters, no output schema, and moderate complexity, the description covers the main use case but omits details about return format or typical output fields. It could be more complete by describing what each result entry contains.

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 description adds meaning beyond the schema by explaining the purpose of drug_class with examples, clarifying that typical_specialties overrides the built-in set, and noting state accepts comma-separated codes. With 71% schema coverage, the description provides valuable additional context.

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 finds Medicare Part D prescribers outside typical specialties, using terms like 'off-specialty early adopters' and providing an example. It distinguishes from sibling tools like prescribers_partDBrandShareShift_search by focusing on atypical specialty rather than brand share or year-over-year delta.

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 explains when to use the tool (to find off-specialty prescribers) and lists filtering options, but does not explicitly state when not to use it or suggest alternatives. The context is clear, but exclusions are missing.

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