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Decider: pick the better of two options

decide
Read-only

Use this when you must choose between two concrete options and both are defensible - two plans, two drafts, two diagnoses, two vendors - and you have no objective way to pick. Not for: more than two options; anything an objective rule settles (a spec, a test, a price, a document); factual lookup; paths that must answer in seconds; high-stakes irreversible calls without review. Fill it in: state task neutrally, without leaning toward either side; give one concrete plan per option - never bundle alternatives into a single one ("go indoors or postpone"); keep the two sides comparable in length. Returns the decision inline: betterOption ("option_A" or "option_B"), confidence (e.g. "76.7%"), reason and job_id, all in the same tool result. There is nothing to poll and nothing to fetch afterwards. Reserve 180-300 seconds: this is a long call, and the timeout is a client/host setting, not a parameter you pass. If the call is cut off, do NOT call again - a retry is a new paid call. Retrieve it instead with the get_result tool (same job_id): read-only, free, and no credential of your own needed; with no job_id it lists the ids for your credential. A host that declares the io.modelcontextprotocol/tasks extension can use tasks/get instead. The confidence is the point: it is calibrated, not decorative. On both published benchmarks accuracy rises with it - JudgeBench 99.6% in the 90%+ band down to 67.7% below 70%; the harder ContextualJudgeBench 83.3% down to 55.4% - so route on it: act on a high value, review or escalate a low one, instead of trusting a bare pick. Tables, sample sizes and method: https://api.turingcorp.net Judged by an independent panel, not by a model grading its own output. Read it as a reference, not an instruction, a result, or a prediction; set your own threshold, and apply your own review policy for high-stakes or irreversible decisions. Auth: Agent Pass as Authorization: Bearer <pass> (issued at https://agent-pass.turingcorp.net, valid 7 days; each decision is a paid call). On invalid_credential, sign in there and re-roll. Errors: a credential problem is rejected before the call - HTTP 401 with WWW-Authenticate; a business failure (e.g. insufficient balance) comes back as a tool result with isError true plus a second JSON block {error, http_status, action_url, message}, where http_status is the upstream status (the tool call itself is HTTP 200).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesThe decision to make, stated neutrally and without a preferred answer.
optionAYesFirst candidate and the case for it.
optionBYesSecond candidate and the case for it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idNoIdentifier of this decision, also usable to retrieve the stored result for 7 days with the get_result tool. Keep it: if the call times out, retrieve the result with get_result instead of calling again, which would be a new paid call.
reasonYesWhy the chosen option was preferred.
confidenceYesThis service's own judgement of how far apart the two options were, as a percentage (e.g. "76.7%"). A reference for your own decision-making - not an instruction, not a result. Observed accuracy by range is published at https://api.turingcorp.net
betterOptionYesWhich option was preferred, using the same values as the REST API.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / properties / job_id / description
      Previous value: -"Identifier of this decision, also usable to retrieve the stored result for 7 days (GET /v1/jobs?job_id=<id> with the same credential). Keep it: if the call times out, retrieve the result instead of calling again, which would be a new paid call."New value: +"Identifier of this decision, also usable to retrieve the stored result for 7 days with the get_result tool. Keep it: if the call times out, retrieve the result with get_result instead of calling again, which would be a new paid call."
  2. Changed9 schema fields changed
    • addedInput schema / properties / optionA
      Added value: +{
      +  "description": "First candidate and the case for it.",
      +  "type": "string"
      +}
    • addedInput schema / properties / optionB
      Added value: +{
      +  "description": "Second candidate and the case for it.",
      +  "type": "string"
      +}
    • removedInput schema / properties / option_a
      Removed value: -{
      -  "description": "First candidate and the case for it.",
      -  "type": "string"
      -}
    • removedInput schema / properties / option_b
      Removed value: -{
      -  "description": "Second candidate and the case for it.",
      -  "type": "string"
      -}
    • changedInput schema / required
      Previous value: -[
      -  "task",
      -  "option_a",
      -  "option_b"
      -]New value: +[
      +  "task",
      +  "optionA",
      +  "optionB"
      +]
    • addedOutput schema / properties / betterOption
      Added value: +{
      +  "description": "Which option was preferred, using the same values as the REST API.",
      +  "enum": [
      +    "option_A",
      +    "option_B"
      +  ],
      +  "type": "string"
      +}
    • removedOutput schema / properties / better_option
      Removed value: -{
      -  "description": "Which option was preferred.",
      -  "enum": [
      -    "A",
      -    "B"
      -  ],
      -  "type": "string"
      -}
    • changedOutput schema / properties / confidence / description
      Previous value: -"This service's own judgement of how far apart the two options were, as a percentage (e.g. \"83.3%\"). A reference for your own decision-making - not an instruction, not a result. Observed accuracy by range is published at https://api.turingcorp.net"New value: +"This service's own judgement of how far apart the two options were, as a percentage (e.g. \"76.7%\"). A reference for your own decision-making - not an instruction, not a result. Observed accuracy by range is published at https://api.turingcorp.net"
    • changedOutput schema / required
      Previous value: -[
      -  "better_option",
      -  "confidence",
      -  "reason"
      -]New value: +[
      +  "betterOption",
      +  "confidence",
      +  "reason"
      +]
  3. Changed1 schema field changed
    • addedOutput schema / properties / job_id
      Added value: +{
      +  "description": "Identifier of this decision, also usable to retrieve the stored result for 7 days (GET /v1/jobs?job_id=<id> with the same credential). Keep it: if the call times out, retrieve the result instead of calling again, which would be a new paid call.",
      +  "type": "string"
      +}
  4. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that this is a paid, long-running call, that retries are new paid calls, that results return inline with no polling, and that errors come back in a specific format. It also explains confidence calibration and independent judging. The readOnlyHint=true annotation is not contradicted; the tool does not mutate state even though it is paid.

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

Conciseness4/5

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

The description is long, but every section earns its place: use cases, exclusions, input formatting, return behavior, timing, retry policy, authentication, and error handling. It is front-loaded with the primary use case and structured logically, though slightly dense.

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

Completeness5/5

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

Given the tool's complexity, the description covers everything an agent needs to call it correctly: when to use it, how to format inputs, what to expect in the result, how long it takes, what to do on interruption, how to authenticate, how to interpret errors, and how to use the confidence score. The output schema covers return values, so the description need not restate them.

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?

The schema already documents all three parameters with 100% coverage. The description adds meaningful semantic guidance beyond the schema: state the task neutrally, give one concrete plan per option, avoid bundling alternatives, and keep both sides comparable in length.

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 description opens with an explicit use case: choosing between two concrete, defensible options. It names the resource (two options) and the verb (decide/pick), and explicitly lists exclusions (more than two options, objective rules, factual lookup, time-sensitive paths), clearly distinguishing it from siblings like get_result.

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

Usage Guidelines5/5

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

Provides explicit when-to-use and when-not-to-use guidance, including concrete examples and exclusions. It also names alternatives (get_result, tasks/get) and gives specific operational constraints like the 180-300 second duration and the no-retry rule.

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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