find_equivalent

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

Annotations indicate read-only, non-destructive, idempotent, open-world behavior. The description adds valuable context: lists searched terminologies, explains the subtraction logic between source and target, and confirms no contradiction with 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?

Concise, well-structured description with bullet points. Every sentence adds value, front-loaded with the main purpose, and no redundant information.

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 presence of an output schema, the description adequately covers usage, parameter interactions, and behavior. No additional context needed for this complexity level.

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?

All three parameters are fully described in the schema (100% coverage). The description adds extra meaning by explaining how source_terminology and target_terminologies interact via subtraction, which is not clear from schema alone.

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 action ('search for equivalent terms') and the resource ('multiple medical terminologies'). It distinguishes from siblings by specifying cross-terminology mapping, unlike single-terminology lookups.

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?

Provides explicit when-to-use context with bullet points, explains parameter logic (target_terminologies to limit, source_terminology to exclude), and gives a concrete use case ('when you already have a code from that terminology').

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