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

TableJSON 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	Platform admins only: select an organization for this operation. Required when changing another organization’s study or using its wallet.
`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

TableJSON 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 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

A4.8/5.0

Behavior5/5

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

Annotations only supply the generic profile (readOnlyHint=false, openWorldHint=true, idempotentHint=false). The description goes well beyond: it clarifies this produces a draft rather than a live study, lists the implicit defaults (voice interview, English, Elliot) applied on omission, states cross-parameter constraints (synthetic respondents require chat; prototype-tests require video or voice, never chat), and warns against a delegating model fabricating human confirmation of recruiting_method — a genuine behavioral/policy disclosure an agent could not infer elsewhere.

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?

Purpose and the recruiting_method precondition are front-loaded, and almost every sentence carries operational content. It is nevertheless dense and slightly repetitive: the concept/prototype asset instructions restate what customize_study already owns, and the closing 'Voice configuration is kept for chat as well as voice and video' duplicates the schema's own voice description.

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?

For an 8-parameter, open-world creation tool with an output schema present, the description covers the full workflow an agent needs: create the draft here, then hand the natural-language brief and any concept/prototype assets to customize_study, with the required asset fields enumerated per study type. Return values are correctly left to the output 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 88%, so the schema already carries most parameter documentation (including the voice/language/format defaults). The description still adds meaning beyond the schema by supplying cross-field constraints, e.g. 'Synthetic respondents require chat' and the prototype-must-not-be-chat rule, and by framing recruiting_method as a human-confirmation requirement rather than a plain enum. It does not, however, add much on name, idempotency_key, or organization_id.

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?

Names a specific verb (Create) and resource (study) and enumerates the three supported study modes, then states the boundary: 'using ordinary metadata only' and 'Do not draft or pass the study plan, audience targeting, screener questions... here.' It distinguishes itself from the nearest sibling by routing brief customization to customize_study, so an agent can pick between the two without opening schemas.

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 explicit when-to-use rules per study type ('For a concept test... For a prototype test...'), an explicit alternative (customize_study for the research brief, concept images, prototype assets), and hard preconditions (recruiting_method must be an explicit human choice). It also names the exceptions ('Unless the human requests otherwise').

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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