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

Annotations already establish readOnlyHint=true, so the safe read-only nature is covered structurally. The description adds value by disclosing the specific composition of the response, including the unusual rawOpportunityScore behavior that differs from list_opportunities. No contradictions or hidden side effects are present.

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, front-loaded sentence conveys the tool's purpose and key output details without filler. Every element adds useful information, and the normalization caveat is placed at the end where it naturally complements the enumerated response contents.

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?

Although there is no output schema, the description enumerates the major return components in specific terms, making the expected result clear. The main gap is parameter guidance, but the schema covers context and the IDs are strongly implied by the tool name and cluster terminology.

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 only 33%, and the description does not compensate by explaining clusterId, projectId, or context. The context parameter is described in the schema, but the other two required parameters have only format constraints, leaving their semantic roles to be inferred from the tool name and general wording.

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 uses a specific verb-resource pair ('Get a cluster detail') and enumerates exactly what the response contains: top-20 keywords, top-10 ranked pages, top-5 competitors, article suggestions, and rawOpportunityScore. It also distinguishes itself from list_opportunities by calling out the normalized vs raw score difference, which removes ambiguity.

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 explicitly names list_opportunities as the alternative and explains the key difference (raw vs normalized score), giving the agent a concrete basis for selecting this tool. It does not provide an explicit 'use this when...' statement or broader exclusions, but the comparison to a sibling tool provides clear context.

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