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Minds: Synthetic Market Research

Audience creation progress

get_audience_creation_progress
Read-onlyIdempotent

Reads progress and never starts or retries anything: an Audience creation by operationId, with its members’ training; or an existing Audience by audienceId, with its member training and background research, or with recalibrationId one recalibration’s status, retained result or terminal error. Validation needs 10 ready members; for a final score wait until all are trained and research is done.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audienceIdNoAn existing Audience, instead of operationId.
operationIdNoAudience creation operation id.
recalibrationIdNoWith audienceId: the operation id returned by recalibrate_audience.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
audienceIdNoExisting Audience read by audienceId.
audienceCreationNoCurrent Audience creation and member training snapshot.
audienceProgressNoExisting Audience member readiness, background research and coverage.
audienceRecalibrationNoOne recalibration receipt: id, status, progress, retained result or terminal error.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changed
    • addedInput schema / properties / audienceId
      Added value: +{
      +  "description": "An existing Audience, instead of operationId.",
      +  "format": "uuid",
      +  "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
      +  "type": "string"
      +}
    • addedInput schema / properties / operationId / description
      Added value: +"Audience creation operation id."
    • addedInput schema / properties / recalibrationId
      Added value: +{
      +  "description": "With audienceId: the operation id returned by recalibrate_audience.",
      +  "format": "uuid",
      +  "pattern": "^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-8][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}|00000000-0000-0000-0000-000000000000|ffffffff-ffff-ffff-ffff-ffffffffffff)$",
      +  "type": "string"
      +}
    • removedInput schema / required
      Removed value: -[
      -  "operationId"
      -]
    • addedOutput schema / properties / audienceId
      Added value: +{
      +  "description": "Existing Audience read by audienceId.",
      +  "type": [
      +    "string",
      +    "null"
      +  ]
      +}
    • addedOutput schema / properties / audienceProgress
      Added value: +{
      +  "description": "Existing Audience member readiness, background research and coverage."
      +}
    • addedOutput schema / properties / audienceRecalibration
      Added value: +{
      +  "description": "One recalibration receipt: id, status, progress, retained result or terminal error."
      +}
  2. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive. The description adds real value on top: it enumerates what each mode surfaces (members' training, background research, retained result or terminal error) and the readiness condition for validation and final scores. It stops short of describing polling cadence or whether progress is eventually consistent.

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?

Front-loaded with the scoping statement ('reads progress and never starts or retries anything'), then the three lookup modes, then the readiness rule. Dense but every clause carries information; the mid-sentence list structure is slightly harder to parse than necessary.

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?

Covers all three identifier modes, the readiness requirements, and what each path returns; an output schema exists so return format need not be restated. Missing only secondary operational details such as whether repeated polling is expected or how stale results may be.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds relational semantics the schema does not: recalibrationId only makes sense 'with audienceId', and it is the operation id returned by recalibrate_audience. That pairing constraint is genuinely useful invocation guidance.

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?

States a specific verb (reads progress) and resource (Audience creation / member training / recalibration), and immediately clarifies it 'never starts or retries anything', distinguishing it from start_study_run, resume_study_run, and recalibrate_audience. An agent can tell what it returns 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 Guidelines5/5

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

Explicitly routes by identifier: operationId for an in-flight creation, audienceId for an existing Audience, audienceId+recalibrationId for one recalibration's status. States the negative case (it never starts or retries) and gives an operational readiness rule ('Validation needs 10 ready members; for a final score wait until all are trained and research is done').

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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