consensus

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

With no annotations, the description carries the full behavioral burden and fails it: nothing is said about cost/latency of multi-model calls, whether responses are aggregated or returned raw, default model count, or authorization needs. 'Independent' hints at isolation but is not explained.

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 short but by under-specification, not efficiency; it is a sentence fragment with no front-loaded statement of what the call returns or requires. Length is not the problem — content is.

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?

A 4-parameter tool with 0% schema coverage, no annotations, and no output schema receives essentially no supporting description. Nothing an agent would need to call it correctly — required prompt, model count semantics, ID parameters — is covered.

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 0% across 4 parameters. The description's 'multiple ... models' loosely gestures at the models integer (min 2, max 5) but never states the range, and mission_id/project_id are entirely unexplained, so parameter meaning is left undocumented.

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 fragment 'Ask multiple independent models/reviewers' conveys the core idea of querying several models, which is more than the bare name 'consensus' provides, but it is a phrase rather than a stated verb+resource and gives no scope. It does nothing to distinguish this tool from siblings like delegate or swarm_run, which also involve model invocation.

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?

There is no when-to-use guidance, no indication of when consensus is preferable to delegate or swarm_run, and no prerequisites. The agent must guess the selection context entirely.

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