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gwmage

Rootr MCP Server

Create a Rootr form

rootr_create_form

Create a fillable intake form in a Rootr workspace, optionally seeding fields and mirroring responses to a database.

Instructions

Create a new FORM node (fillable intake) in a Rootr (루터) workspace, optionally seeded with field definitions. Use FORM for surveys/request queues collected from people outside the tree — set targetDatabaseId to also mirror each response into a DATABASE's rows. Fields are typed inputs shown to respondents: text | textarea | number | select | multi_select | checkbox | date; select/multi_select need options ({name,color}[]). Read the form first (rootr_read_form) before updating so you keep each field's id stable — response values are keyed by field id, so renaming/dropping an id orphans past responses' answers for that field.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
iconNoEmoji icon for the node
nameNoForm name/title
configNoFree-form form config object (e.g. publicSubmit mode)
fieldsNoInitial field definitions; defaults to an empty form
parentIdNoParent folder/node id to create it under
workspaceNoWorkspace id; defaults to ROOTR_WORKSPACE/config if omitted
targetDatabaseIdNoDATABASE node id whose rows should mirror this form's responses
Behavior5/5

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

Annotations indicate non-readonly, non-destructive. Description adds critical context: field type details, options structure, id stability warning, and the effect of targetDatabaseId. No contradictions with annotations.

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?

Single paragraph is dense but well-organized: purpose first, then usage hints, then parameter details and a warning. No wasted sentences; could benefit from slight structuring.

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 complexity (7 params, nested objects, no output schema), description covers essential behavior: creation, field types, options, id management, and response mirroring. Provides enough context for correct usage.

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 100%, baseline 3. Description adds meaning by explaining field types, options requirements, id stability, and the purpose of targetDatabaseId, going beyond schema descriptions.

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 creates a new FORM node (fillable intake) in a Rootr workspace, optionally seeded with fields. It specifies use for surveys/request queues, distinguishing it from sibling tools like rootr_read_form or rootr_update_form.

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?

Provides guidance on when to use FORM (surveys/request queues) and mentions setting targetDatabaseId to mirror responses. Advises reading the form before updating to keep field ids stable, but does not explicitly contrast with other creation tools.

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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