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

Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint=false), so the description's main behavioral contribution is the data vintage disclosure ('2026q3, v322r0') and the guarantee that responses always state the vintage and resolved setting. This is valuable transparency beyond annotations, though it does not explain rate limits or error behavior.

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 front-loaded with the core question and answer, then provides supporting details about the data source and return behavior. It is slightly verbose with multiple parenthetical qualifications, but every sentence contributes useful context without excessive repetition.

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 absence of an output schema, the description adequately explains what the tool returns (modifier indicator categories) and the data vintage. However, it could more explicitly describe the response structure or edge cases (e.g., what happens with invalid codes, or how the 'setting' parameter interacts with results in more detail).

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 each parameter clearly documented in the schema (including an enum-like description for 'setting'). The description does not add additional meaning to the parameters beyond what the schema provides, so baseline 3 is appropriate.

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 a specific question-domain ('Can two procedure codes be billed together on the same day?') and names the exact data source (CMS NCCI PTP edits) and return value (modifier indicator). It clearly distinguishes itself from siblings like explain_ncci_edit by focusing on pair-level billing checks rather than edit explanations.

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 explicit trigger phrases ('can I bill 99214 and 93000 together', 'is there an NCCI edit between these two codes', 'do I need a modifier for this code combination') that tell an agent exactly when to invoke this tool. It also clarifies what a negative result means ('a pair not found here has never had a CMS-recorded PTP edit'), which helps the agent interpret outcomes.

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