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decide_many

Read-onlyIdempotent

Ask multiple independent questions about a single state in one model call. Get calibrated judgments for choices, scores, or yes/no probabilities to resolve ambiguous decisions cheaply.

Instructions

Ask several independent questions about ONE state in a single pass. Question ids stay local, so N questions cost one model call, not N — this is the cheap way to get many judgments at once. Types: 'choice' (label + criteria map), 'score' (ordered list of 2-10 steps), 'noul' (a yes/no, returns P(true)).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateYesThe situation: a string, or an object of named facts.
backendNo
questionsYesquestion name -> {type, instructions, criteria}
state_labelNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
usageNo
answersYesquestion name -> answer
backendYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value on top: question ids stay local to the call, 'noul' returns P(true), and 'score' expects an ordered list of 2-10 steps. These are behavioral facts beyond the structured fields and are consistent with the annotations.

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

Conciseness5/5

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

Three dense sentences, zero filler. The core purpose is front-loaded in sentence one, the cost justification in sentence two, and the type semantics in sentence three. Every sentence earns its place.

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

Completeness4/5

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

Given an output schema exists (so return values needn't be described) and annotations cover the safety profile, the description covers the main usage pattern and the tricky question-type semantics. The only gaps are not naming the sibling decide for explicit routing and not explaining backend, but for a complex nested-parameter tool this is reasonably complete.

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

Parameters4/5

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

With schema coverage at 50%, the description must compensate, and it meaningfully does for the most complex parameter. It explains the three question types and their criteria shapes ('choice' label+criteria map, 'score' ordered 2-10 steps, 'noul' returns P(true)), which the schema only enumerates. It adds nothing about backend or state_label, but the questions parameter is the one that needed the semantics.

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

Purpose5/5

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

The first sentence states a specific verb+resource: 'Ask several independent questions about ONE state in a single pass.' It also distinguishes itself from the sibling decide by emphasizing the N-questions-one-call batching and 'cheap way' framing, so an agent can tell this is the multi-question counterpart without opening the schema.

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

Usage Guidelines4/5

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

The description gives clear context for when to use it: when you have several independent questions and want to save model calls ('N questions cost one model call, not N'). The 'independent' qualifier implicitly warns against batching dependent questions. However, it never names the alternative tool (decide) explicitly, nor states a when-not-to-use condition.

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

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