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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds valuable context: 'No auth — US National Library of Medicine public domain, unlimited free.' It also explains the classification type (primary stem code vs extension modifier), providing clarity beyond the schema. This adds meaningful behavioral context without contradicting 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 well-structured and concise. It front-loads the core purpose, then lists outputs, use cases, examples, and auth info. Every sentence adds value: no fluff, no repetition. It is compact yet informative, ideal for an AI agent to parse quickly.

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 single-parameter lookup tool with annotations covering read-only/idempotent behavior and an output schema in place, the description is fully complete. It covers purpose, usage, examples, and auth/free status. Nothing essential is missing for an agent to call this tool correctly.

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%—the 'code' parameter is thoroughly described with examples in the schema itself. The description mentions example codes but does not add new parameter semantics beyond what the schema already provides. Baseline of 3 is appropriate since the schema does the heavy lifting.

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's purpose: 'Retrieve the title and classification type for a specific ICD-11 code.' It specifies the output (human-readable name and classification type) and provides concrete examples (BA00, 5A10, CA40). This makes it unambiguous and distinguishes it from the sibling search/autocomplete tools by emphasizing 'specific code' lookup.

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 gives explicit use cases: 'Use to validate ICD-11 codes, decode alphanumeric codes in clinical records, or verify correct code usage.' This tells the agent when to invoke this tool. However, it does not explicitly mention alternatives or when to avoid it, though the context of siblings with search/autocomplete is implicit. Slight gap in exclusion guidance.

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