Minds: Synthetic Market Research

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

Name	Required	Description
`files`	No
`existingFiles`	No
`groundingJson`	No	Optional 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.
`conversationFiles`	No	Research files (text, Markdown, CSV, JSON) imported like existingFiles; in sourceIdx order they follow existingFiles and precede files. Files shared in this conversation: uploaded or generated images, PDFs, documents. Each is copied into Minds storage on receipt; its file_id is its attachment id.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No	Import result from the Minds API: accepted sources and their processing state.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 1, 2026

addedInput schema / properties / conversationFiles

Added value: +{
+  "description": "Research files (text, Markdown, CSV, JSON) imported like existingFiles; in sourceIdx order they follow existingFiles and precede files. Files shared in this conversation: uploaded or generated images, PDFs, documents. Each is copied into Minds storage on receipt; its file_id is its attachment id.",
+  "items": {
+    "properties": {
+      "download_url": {
+        "description": "Download URL the chat host supplies for this file.",
+        "minLength": 1,
+        "type": "string"
+      },
+      "file_id": {
+        "description": "The chat host's ID for this file.",
+        "minLength": 1,
+        "type": "string"
+      },
+      "file_name": {
+        "description": "File name when the host supplies it.",
+        "minLength": 1,
+        "type": "string"
+      },
+      "mime_type": {
+        "description": "MIME type when the host supplies it.",
+        "minLength": 1,
+        "type": "string"
+      }
+    },
+    "required": [
+      "download_url",
+      "file_id"
+    ],
+    "type": "object"
+  },
+  "type": "array"
+}

Changed1 schema field changedSep 20, 2026

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"
+}

AddedSep 10, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations establish the safety profile (readOnly=false, idempotent=true, destructive=false), so the bar is lower. The description still adds real value beyond them: retry safety, the no-Audience/no-Minds side-effect boundary, and the absence of independent verification of supplied percentages. Auth requirements and limits are not mentioned, keeping it from a 5.

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?

Four sentences, each carrying distinct information, with the core action and input constraint front-loaded. The middle sentences about grounding JSON and source ordering are dense but earn their place; slightly tighter phrasing could improve scanability.

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?

For a mutation-style ingestion tool with an output schema, the definition covers inputs, ordering semantics, idempotency, and non-effects well. Remaining gaps are operational details (permissions, size/item limits) that an agent might want before calling.

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 only 50%, so the description must compensate, and it does for the critical parts: file-contents-not-paths for 'files', and the source binding order of existingFiles, then files, then conversationFiles in sourceIdx order. It does not clarify maxItems/count limits or the 5MB content cap, so it is not fully compensating.

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 and resource ('Imports ... research files into account-owned storage') plus accepted formats and the key constraint that it takes file contents rather than paths. An agent can immediately separate this ingestion tool from siblings like create_audience_from_brief or plan_study_questions.

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?

Gives clear context for when the tool applies (supplying file contents, optional grounding JSON for preview/creation) and explicitly scopes it out of audience/mind creation and web search. It never names a sibling alternative for the excluded cases, so it falls just short of an explicit when/when-not routing statement.

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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