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

With no annotations, the description carries full burden. It discloses the tool reads public CMS data, is not a consumer report, and costs $0.1/call. It explains the behavioral logic for new_entrant (max_prior_claims) and de_adopter (min_pct_drop). No destructive behavior is implied, and transparency about pricing and data source is helpful.

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, with five sentences that each add essential information. It front-loads the purpose, then explains directions, filters, data source, and pricing in a logical order. No redundant or extraneous content.

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 tool has 10 parameters and no output schema, the description covers the core behavior, filtering options, and data source. It mentions that the tool returns NPIs for each direction. However, it does not describe the output format or pagination details (limit/offset), which would be helpful for completeness.

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 80%, so baseline is 3. The description adds significant value beyond schema by explaining the 'switchable moment' concept, detailing the criteria for each direction (e.g., ≤max_prior_claims for new_entrant), and providing example values for drug_class. This enriches the context for parameter usage.

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 prescribers entering or leaving a Part D therapeutic class year-over-year (PY2023→PY2024). It specifies the two directions (new_entrant and de_adopter) and contrasts with sibling tools focused on other prescriber analytics, making the purpose distinct and unambiguous.

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 provides clear context ('switchable moment for a pharma team') and explains when to use each direction parameter. It lists filterable attributes (drug_class, state, specialty) and notes data source and pricing. However, it lacks explicit when-not-to-use guidance or alternative tool recommendations.

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