discover_entities

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

With no annotations, the description carries full burden. It discloses the return value as 'a catalog of Semantic Entities with descriptions of their fields' and implies a read-only discovery operation. However, it does not mention potential limits, entity visibility, or data freshness, which would provide richer behavioral context.

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?

Two concise sentences with no filler. The key directive is front-loaded ('Use this tool FIRST') and each sentence earns its place by covering what, when, and what to expect.

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 zero parameters, no output schema, and a simple discovery use case, the description covers all necessary aspects: purpose, usage timing, and return content. The only minor gap is not naming the sibling directly, but the 'FIRST' and 'for querying' phrasing sufficiently implies the distinction.

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 tool has zero parameters, so the baseline is 4 according to the rubric. The empty input schema fully covers parameter documentation, and the description correctly adds no unnecessary parameter details.

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?

States a clear verb and resource: 'Discover available Data Assets (Entities)' and explains its role as understanding the schema (Dimensions and Measures). It differentiates from the sibling by positioning itself as a prerequisite to querying, though it does not name execute_query explicitly.

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?

Explicitly instructs to use this tool FIRST to understand the schema before querying, giving clear context of when it should be used. It does not state exclusions or directly name the alternative tool, which prevents a 5.

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