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Userology-Inc

Userology MCP Server

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update_section

Update a section's name, description, prototype link, or Figma link within a study by specifying study and section IDs, keeping research data accurate.

Instructions

Update a section's name, description, prototype link, or Figma link.

Args: study_id: The unique identifier of the study. section_id: The unique identifier of the section/task. name: New name for the section. description: New description for the section. prototype_link: URL of the prototype associated with this section. figma_link: Figma file URL for the section.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
study_idYes
figma_linkNo
section_idYes
descriptionNo
prototype_linkNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses the update action but does not clarify whether it performs a partial or full update, what happens when the section doesn't exist, or any side effects/permissions required.

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?

The description is concise and well-structured: a clear opening sentence followed by a parameter list. The list is necessary because the schema lacks descriptions, so every line earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 6 parameters and is a mutating operation with no annotations or schema-level descriptions. The description covers purpose and parameters, but lacks behavioral details (e.g., partial update behavior, existence checks) and usage prerequisites, leaving some gaps for a complete understanding.

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?

The description provides one-line explanations for each parameter (e.g., 'The unique identifier of the study'), adding meaning that the input schema lacks (schema_description_coverage is 0%). It clarifies the intended format for prototype_link and figma_link, though it doesn't address edge cases like empty-string semantics.

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 clearly states the tool's function with a specific verb ('Update'), a resource ('section'), and the exact fields affected (name, description, prototype_link, figma_link). This distinguishes it from sibling tools like create_section, get_section, and delete_section.

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 implies usage for updating an existing section's attributes, which is clear context. However, it does not explicitly mention exclusions or when to use alternatives like create_section or get_section.

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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