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build_consensus

Sets up a consensus by selecting eligible free-model voters and defining a synthesis route to answer a given question.

Instructions

Prepare all eligible free-model voters and a synthesis route before Working.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
votersNo
qualityNobalanced
questionYes
allow_paidNo
reasoning_effortNo
excluded_providersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

D1.5/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description gives no information about side effects, whether the tool performs reads or writes, permissions required, reversibility, or what happens to the 'voters' and 'synthesis route' after preparation. It is entirely opaque regarding behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is structurally minimal, but it is under-specified rather than concise. It lacks front-loaded actionable information and does not earn its brevity by conveying essential details; it is more a placeholder than a helpful summary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six parameters, one required, and no annotation or schema description, the tool requires substantial explanation. The description provides almost no context about inputs, outputs, side effects, or usage, making it incomplete for an agent to call the tool correctly. The presence of an output schema does not compensate for the missing operational context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, meaning the schema provides no parameter explanations, and the description also fails to explain any of the six parameters (question, voters, quality, allow_paid, reasoning_effort, excluded_providers). The description adds no meaning beyond the raw field names, leaving agents to guess parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states an action 'Prepare' and a resource 'eligible free-model voters and a synthesis route', but it is vague about what 'prepare' entails and what the tool ultimately does. It does not mention the primary required parameter 'question' or any concrete outcome, so an agent cannot clearly infer the tool's purpose or differentiate it from siblings like 'prepare_task' or 'route_task'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only usage hint is 'before Working', which implies it is a prerequisite step, but it does not specify when to use this tool versus alternatives, nor does it mention any exclusions or conditions. There is no guidance on when not to use it or how it fits into a broader workflow.

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