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Minds: Synthetic Market Research

by ai.getminds
OverviewDiscussionsAdmin

Import Audience Research Sources

import_audience_sources
Idempotent

Imports supplied UTF-8 text, Markdown, CSV and JSON research files into account-owned storage. Accepts file contents rather than local paths. Identical file imports are safe to retry. Optional caller-reviewed grounding JSON binds distributions to existingFiles followed by files in sourceIdx order, returning a normalized snapshot and checksum for audience preview and creation. This operation creates no Audience or Minds and performs no web search or independent verification of supplied percentages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNo
existingFilesNo
groundingJsonNoOptional explicitly supplied distribution JSON (the grounding object, not respondent rows). Sources are bound to the files in request order: existingFiles followed by files. Import does not assert independent verification of the supplied percentages.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoImport result from the Minds API: accepted sources and their processing state.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": {},
+  "properties": {
+    "data": {
+      "description": "Import result from the Minds API: accepted sources and their processing state."
+    }
+  },
+  "type": "object"
+}
  2. Added

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate idempotence and non-destructiveness; the description reinforces this with 'Identical file imports are safe to retry' and adds material behavioral caveats: it creates no Audience or Minds, performs no web search, and does not independently verify supplied percentages. It also discloses the return of a normalized snapshot and checksum.

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 with no filler; every statement earns its place. Key constraints are front-loaded, such as accepted formats, inline content, retry safety, and the no-verification caveat.

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 3-parameter schema, output schema, and annotations, the description is complete enough for an agent to invoke it correctly. It covers parameter intent, ordering, side-effect boundaries, safety, and even foreshadows the normalized snapshot and checksum return without duplicating the output schema.

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

Parameters5/5

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

Only 33% of schema properties carry descriptions, but the description compensates well. It explains acceptable file formats and inline content, names and orders the binding of existingFiles followed by files, and frames groundingJson as optional caller-reviewed distribution JSON. This adds real meaning beyond the raw schema.

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 opening sentence names a specific verb ('Imports'), a clear resource ('UTF-8 text, Markdown, CSV and JSON research files'), and the destination ('account-owned storage'). It also distinguishes itself from audience-creation siblings by explicitly stating it 'creates no Audience or Minds.'

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 practical invocation context: callers must supply file contents rather than local paths, may pass optional grounding JSON, and can safely retry identical imports. It does not name sibling alternatives or provide explicit 'use this when' conditions, but the boundaries are clear enough because it states what the operation does not do.

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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