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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds valuable behavioral guarantees beyond that: results never invent confidence scores, ordering is canonical, and calling with a capabilityId returns inputContract details such as allowed field names, scalar types, constraints, meaning, and required state.

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?

Three sentences, each with distinct value: purpose and scope, execution workflow and return guarantees, and ordering plus anti-hallucination behavior. No filler or redundant restatement of the schema.

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 search tool with 7 optional parameters and nested objects, the description covers the core workflow and critical output behavior. It does not mention pagination or how to use advanced filters, but those are optional and their schema names are reasonably self-explanatory. With an output schema present, the absence of return-structure detail is acceptable.

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 coverage is only 43%, so the description carries a burden it partially meets. It clarifies the roles of query, aiId, and capabilityId, but it does not explain filters, context, cursor, or limit. The schema names hint at their purpose, but the description leaves those to inference rather than compensating for the low coverage.

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 opens with a specific verb and resource: 'Find executable public Darwin capabilities.' It distinguishes the tool from its sibling by framing it as a pre-execution lookup step that returns exact capability IDs and revisions, and by the contrast with the sibling name execute_darwin_capability.

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?

It gives three concrete invocation modes: natural-language query, aiId to browse one AI, and capabilityId for exact lookup. It also states when to call it relative to execution ('before Act'). It does not explicitly list exclusion cases, but the context is clear enough for selecting this tool over execution.

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