explainQuery

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

The tool's annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=falseais. The description adds meaningful behavioral context beyond annotations: it confirms no execution occurs, details what the dry-run returns for each kind (resolved_plan, plan_hash, invocation_hash, etc.), and notes the login requirement with offline operation afterward. This is exactly the kind of context that aids correct invocation.

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 compact yet information-dense. The first sentence states the core purpose immediately. The second sentence adds specific return artifacts for both kinds, a usage directive, and a prerequisite, with no filler. The structure is front-loaded and every clause earns its place.

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 the tool's two distinct modes and complex schema, the description covers both modes completely, specifies what results to expect, explains when to use it, and notes environmental requirements. It does not need to explain return values because there is no output schema, and it correctly avoids redundancy with the input schema. No missing information blocks correct 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 the schema already documents parameters like metric, source, and seed. The description adds semantic value by explaining the role of the 'kind' discriminator and what each kind validates or returns, which is not explicit in the schema. However, it does not go into per-field detail for the spec objects, though the schema covers that thoroughly, so a 4 is appropriate.

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 'Dry-run a queryData request without executing it,' which clearly states the verb, resource, and key constraint. It then explains the two kind variants (query vs computation) and explicitly positions it against queryData, so an agent can distinguish it from the execution tool without needing to compare schemas.

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 gives direct usage guidance: 'Use this to debug clarifications and rejections before running queryData.' This tells the agent when to select this tool over queryDataced and also implies the alternative. It further explains for computation kind what to check (capability existence, signature, seed requirement), covering both branches of behavior.

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