get_entity_catalogue

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

With no annotations, the description carries the full burden. It discloses that the catalogue is filterable and paginated, and that it returns features grouped by product area. It also warns against paging through everything. However, it does not explicitly state that the operation is read-only or describe the response shape, so a small gap remains.

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 two sentences long, front-loads the core definition, and provides actionable guidance without fluff. Every word earns its place, including the parenthetical emphasis on mapping by meaning.

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 read-only listing tool with 5 optional parameters and no output schema, the description provides sufficient context: purpose, filters, pagination, and usage strategy. It does not describe the exact return fields, but that is not strictly necessary for tool selection and invocation.

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%, so baseline is 3. The description adds strategic advice about preferring search/kind filters but does not explain individual parameters beyond what the schema already provides. It adds some context about entities being features grouped by product area, but not enough to raise the score.

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 returns a catalogue of registered entities grouped by product area, with filtering and pagination. It also specifies a concrete use case (picking entity IDs when linking concepts to measured meanings), which distinguishes it from sibling tools like lookup_ontology or get_concept.

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?

Explicit guidance is provided: 'Use this to pick entity ids when linking a concept to what it measures' and 'Prefer search/kind filters over paging through everything.' This tells the agent when to use the tool and the appropriate strategy, fulfilling the dimension well.

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