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

Annotations indicate read-only and non-destructive behavior. The description adds substantial context: the cost+15% pricing model, $0.02 USDC per call SLA, 503 error handling with no charge, and provenance disclosure via data_sources[] and synthesis.output_hash. This goes far beyond 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 dense but well-organized, covering use case, return fields, example, cost, error handling, and provenance. Each sentence adds value without excessive fluff, though it could be marginally streamlined.

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 two-parameter read-only tool with no output schema, the description provides enough context: purpose, output fields, an example, cost, failure behavior, and data source. It is sufficiently complete, though quantity_units semantics could be more explicit.

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 has zero description coverage, so the description must carry the burden. It explains that ndc_or_name takes an NDC (with example 42385096230) and implies quantity_units affects 'optional quantity quote.' However, it does not mention that ndc_or_name may accept a name, and quantity_units is not fully detailed.

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 identifies the tool as providing Mark Cuban Cost Plus Drugs transparent retail pricing for a specific NDC, with expected return fields and an example. This distinguishes it from sibling tools like get_nadac_drug_benchmark, which target different pricing data.

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 explicitly states when to use this tool: 'Use when a patient, benefits manager, or procurement agent needs... transparent retail pricing for a specific NDC.' It provides clear context but does not explicitly mention alternatives or when not to use it, though the niche is sufficiently specific.

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