Run a multi-model debate / cross-validation

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

The description transparently lays out the execution stages, including rounds of critique and the judge's role, which is useful given no annotations. However, it omits side effects, output/return format, and cost/latency implications of invoking multiple providers, and 'one or more rounds' is slightly inconsistent with the schema's minimum of 0.

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 covers the full workflow without filler. Every clause contributes meaning about the debate process.

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 no output schema and no annotations, the description leaves the return contract ambiguous—whether it returns only the judge's final answer or also the debate transcript. It is otherwise adequate for understanding the tool's purpose and required inputs.

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 75%, and the schema already explains question, rounds, and judge defaults. The description adds process-level context for rounds and the judge but provides no additional parameter-specific detail beyond the schema.

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 names a specific process—independent answers, critique rounds, and judge synthesis/selection—with a clear verb and resource. It also differentiates the tool from siblings like run_pipeline and run_orchestrator by emphasizing the multi-provider critique workflow.

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 implies when to use the tool: when a question should be answered and cross-validated by multiple AI providers with a final judge. It does not explicitly state exclusions, prerequisites, or when to prefer a sibling pipeline/orchestrator tool instead.

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