User Intuition

Create Study

create_study

Create an in-depth-interview, concept-test, or prototype-test draft using ordinary metadata only. Ask the human to explicitly choose recruiting_method (panel, BYOP, or synthetic respondents). A value proposed or inserted by a host/delegating model is not human confirmation unless it quotes the human's actual choice. Unless the human requests otherwise, use a voice interview in English with Elliot; these defaults are applied when interview_format, language, or voice are omitted. Synthetic respondents require chat. A prototype-test must use video or voice, never chat. Do not draft or pass the study plan, audience targeting, screener questions, concept links, or concept images here; after creation, send the user's natural-language research brief to customize_study. For a concept test, pass an accessible attachment through customize_study.concept_image or include a publicly downloadable concept-image URL in the message, plus its participant-facing label, stimulus context, audience, and learning goals. For a prototype test, include the prototype URL, participant-facing label, intended tasks, audience, and learning goals. The Customize Plan backend validates and attaches the asset. Voice configuration is kept for chat as well as voice and video.

Input Schema

Name	Required	Description	Default
`name`	Yes
`voice`	No	Interviewer configuration for every format, including chat. Defaults to male when omitted.
`language`	No	Interview language code from userintuition://catalog/languages. Defaults to English (`en`).	en
`study_type`	No	Use concept-test for a participant-facing concept image and prototype-test for a clickable prototype, staging site, live page, or web flow. Prototype tests require video or voice, never chat.	in-depth-interview
`idempotency_key`	No	Reuse the same key and inputs if a prior call timed out. A different operation needs a new key.
`organization_id`	No	Organization for this operation and billing. Use list_organizations to choose an active membership.
`interview_format`	No	Interview mode. Defaults to voice when omitted.
`recruiting_method`	Yes	Required explicit human choice. Ask the user to choose panel, BYOP, or synthetic respondents before calling create_study; do not guess or silently default it.

Output Schema

Name	Required	Description	Default
`result`	Yes	The created study draft. Call get_study for the complete persisted plan.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 22, 2026

changedInput schema / properties / organization_id / description

Previous value: -"Platform admins only: select an organization for this operation. Required when changing another organization’s study or using its wallet."New value: +"Organization for this operation and billing. Use list_organizations to choose an active membership."

Changed1 schema field changedOct 1, 2026

addedInput schema / properties / organization_id

Added value: +{
+  "description": "Platform admins only: select an organization for this operation. Required when changing another organization’s study or using its wallet.",
+  "maxLength": 128,
+  "minLength": 1,
+  "type": "string"
+}

Changed7 schema fields changedSep 30, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

changedOutput schema / properties / result / additionalProperties
```
Previous value: -trueNew value: +{}
```
removedOutput schema / properties / result / properties / dashboard_url / $ref
```
Removed value: -"#/properties/result/properties/name"
```
addedOutput schema / properties / result / properties / dashboard_url / type
```
Added value: +[
+  "string",
+  "null"
+]
```
removedOutput schema / properties / result / properties / study_link / $ref
```
Removed value: -"#/properties/result/properties/name"
```
addedOutput schema / properties / result / properties / study_link / type
```
Added value: +[
+  "string",
+  "null"
+]
```

First observedSep 30, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Goes well beyond the annotations, which only declare it is a non-read-only, non-idempotent, non-destructive write. It discloses the human-confirmation rule and that a host-proposed value does not count, that the Customize Plan backend validates and attaches assets, defaults applied when format/language/voice are omitted, and that voice config persists into chat.

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 purpose and the human-confirmation rule, and nearly every sentence carries operational weight. It is long, with mild redundancy (the closing note that voice config applies to chat restates the schema's own wording) and some asset-handling detail that arguably belongs with customize_study.

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 an 8-parameter creation tool with an output schema, the description covers the pieces an agent could get wrong: mandatory human choice, format/type compatibility, default injection, and handoff to customize_study. Return values need not be explained given the output schema, though billing/organization implications are left entirely to the schema.

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 already 88%, so parameters are largely self-documenting. The description still adds meaning the schema does not: recruiting_method must be a human choice not a guess, and the omission defaults for interview_format, language, and voice. It stops short of explaining organization_id or name constraints, but those are covered in the 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?

States a specific verb and resource with explicit scope: creates a draft study of one of three named types, using only ordinary metadata. It also carves out what the tool does NOT do (study plan, targeting, screeners, concepts) and names customize_study as the place for that, so it is clearly separable from its closest sibling.

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?

Gives concrete when-to-use routing (brief goes to customize_study after creation), hard constraints (synthetic respondents require chat; prototype-test never chat), and default behavior when optional fields are omitted. It also states an explicit precondition — a human must choose recruiting_method — rather than leaving it inferred.

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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