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Userology-Inc

Userology MCP Server

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create_section

Add a new section to a UX research study, specifying its type and position, to structure testing of prototypes, concepts, interviews, or live products.

Instructions

Add a new section to a study.

REQUIRED NEXT STEPS after calling this — do not skip:

  1. Call update_section to set the section's name and description.

  2. Call generate_guide to create the AI interview guide.

  3. Present the generated guide to the user for review.

SECTION TYPES:

  • "prototype": Testing interactive Figma prototypes

  • "conceptTesting": Feedback on mockups or early-stage concepts

  • "voiceInterview": Open-ended discussion, no visual stimulus

  • "liveProductResearch": Testing against a live product URL

Returns: New section object with id, type, and index.

Args: study_id: The unique identifier of the study. section_type: One of 'prototype', 'conceptTesting', 'voiceInterview', 'liveProductResearch'. index: Zero-based position for the new section (default: 0).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexNo
study_idYes
section_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description discloses important behavioral details: the created section is incomplete until update_section is called, and generate_guide must follow. It also notes the return object. This goes beyond a simple 'creates a section' statement, though it does not cover error conditions or prerequisites like a valid study_id.

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?

The description is well-structured with clear sections: purpose, required steps, section types, return value, and parameters. Every sentence contributes useful information, with no filler or repetition. The formatting makes it easy to scan.

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 tool's simple create operation, the description covers all essential aspects: what it does, required follow-up actions, valid section types, parameter semantics, and the return object. It is complete for an agent to invoke the tool and handle the result appropriately.

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?

Despite 0% schema description coverage, the description fully explains all three parameters: study_id, section_type with explicit allowed values, and index with its default. This compensates entirely for the lack of schema documentation and adds contextual meaning.

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 description opens with a specific verb+resource: 'Add a new section to a study.' It clearly differentiates from sibling tools like get_sections, update_section, and delete_section by indicating this is the creation operation. The section type enumeration further clarifies the scope.

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 'REQUIRED NEXT STEPS' section explicitly states that after creation, update_section and generate_guide must be called, giving the agent a clear workflow context. However, it does not explicitly mention when not to use this tool or name alternative tools for non-creation scenarios, so it stops short of a 5.

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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