lookup_ontology

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

With no annotations provided, the description carries the full burden. It discloses significant behavioral detail: case-insensitive substring matching and distinct return payloads for entity, productArea, and concept hits. It does not cover error handling or side effects, but this appears to be a read-only search.

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?

A single well-structured sentence that front-loads the primary action and efficiently describes conditional return behaviors. Every clause adds necessary information without redundancy.

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 3 parameters and no output schema, the description provides a solid map of the response space, covering the main return variants and their fields. It omits ordering/pagination details, but the limit parameter's schema covers max results, so overall completeness is adequate.

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?

The input schema already describes all 3 parameters, but the description adds semantic value: it explains the query interpretation (case-insensitive substring) and how the kind of the matched item changes the response structure. This supplements the schema description of the 'query' parameter.

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 the ontology by name') and specifies matching mode (case-insensitive substring). It distinguishes this tool from siblings like get_concept or list_coverage_gaps by describing different result types (entity, productArea, concept) and what each returns.

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 implies when to use the tool: when searching ontology entries by name and expecting polymorphic results. It doesn't explicitly name alternatives or provide exclusions, but the context makes the primary use case clear.

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