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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: it runs locally, requires no LLM or API key, and describes the two operational modes and their outputs. No contradiction exists.

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 dense but every sentence earns its place: purpose, modes, local execution, CI relevance, input requirements, and sibling routing. It is front-loaded with the core purpose and ends with the alternative tool, which is an effective structure.

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 rich annotations, complete schema, and output schema, the description covers everything an agent needs: what the tool does, when to use it, how modes differ, what inputs are required, and which sibling to choose instead. Nothing essential is missing.

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 100%, so the baseline is 3. The description adds meaningful semantics by explaining the role of the reference parameter and clarifying that responses must be for the same task and can be plain strings or labeled objects. This goes beyond the schema's basic field descriptions.

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's purpose: semantically analyze N model outputs for the same task, with distinct consensus and reference-based modes. It explicitly differentiates itself from the sibling compare_responses, so an agent can disambiguate without inspecting 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?

It gives explicit guidance on when to use the tool versus compare_responses, and explains which mode is appropriate for CI gating versus as a non-failing signal. This is strong, actionable usage context.

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