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

Annotations already mark readOnlyHint=true and destructiveHint=false (safe read), but description adds valuable behavioral context: returns restatement_detected on republish, HTTP 503 no-charge behavior on upstream unavailability, the SLA cost, and data_sources[] provenance. This goes beyond annotations and is specific and useful.

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-structured: use case first, then return fields, an example, source, SLA, error behavior, and data provenance. Each sentence adds value, though the pipe-separated SLA section is a bit of a stylistic shift. It's longer than most but every part earns its place.

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 simple one-parameter read tool with no output schema, the description covers almost everything: the exact return fields, an illustrative example with values and dates, the data source, cost model, error behavior, and provenance. It's fully adequate for an agent to invoke and understand the result.

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 0%, so description must compensate. The parameter name 'ndc_or_name' suggests it accepts an NDC or name, and the example shows an NDC. However, the description doesn't clarify the 'name' form, validation rules, or output format for the parameter beyond that single example. It's minimally adequate but not fully compensating.

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?

Description clearly states the tool returns CMS NADAC drug acquisition cost benchmarks, lists specific fields (NADAC per unit, effective_date, etc.), and provides a concrete example. This distinguishes it from siblings like get_pharmacy_spend_benchmark or get_gpo_contract_benchmark by naming the exact resource (NADAC) and purpose.

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?

Explicitly states when to use: for pharmacy buyers, 340B program managers, or CFO agents needing CMS NADAC benchmarks for contract negotiation or payer comparison. This gives real context but doesn't explicitly mention alternatives or when not to use, just a clear use case.

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