consensus

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the multi-model consensus and execution process, which is useful, but fails to mention critical traits like whether this is a read-only or destructive operation, authentication needs, rate limits, or what 'execute' entails (e.g., running code, side effects). For a tool with execution capabilities and no annotations, this is a significant gap.

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 extremely concise and front-loaded in a single sentence, with zero wasted words. Every element ('4 models generate', 'Claude picks/merges', 'then execute') directly contributes to understanding the tool's workflow, making it efficient and well-structured.

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 complexity (multi-model consensus with execution), lack of annotations, no output schema, and incomplete parameter documentation, the description is insufficient. It omits details on output format, error handling, execution consequences, and how parameters affect the process, leaving the agent with significant gaps for safe and effective use.

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 50% (one parameter has a description, one does not). The description adds no parameter-specific semantics beyond what the schema provides—it doesn't explain 'prompt' or 'architecture' usage, default behaviors, or how they influence the consensus process. With moderate schema coverage, the baseline 3 is appropriate as the description doesn't compensate for the coverage gap.

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: it generates solutions using 4 models, has Claude pick/merge the best one, and then executes. This is specific (verb+resource) and distinguishes it from siblings like 'execute' or 'generate' by mentioning the multi-model consensus process. However, it doesn't explicitly name the resource being acted upon (e.g., 'code' or 'solutions'), which prevents a perfect score.

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 provides no guidance on when to use this tool versus alternatives like 'generate', 'execute', or 'collaborate'. It implies usage for generating and executing code solutions, but lacks explicit when/when-not instructions or named alternatives, leaving the agent to infer context from sibling tool names alone.

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