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gwmage

Rootr MCP Server

Create a Rootr whiteboard

rootr_create_whiteboard

Create a freeform visual canvas for flow diagrams, brainstorming, and journey maps, with optional initial scene.

Instructions

Create a new WHITEBOARD node (a freeform visual canvas) in a Rootr (루터) workspace, optionally seeded with an initial scene. Use WHITEBOARD for flow diagrams, brainstorming, journey maps — not for anything that needs typed/trackable rows (use DATABASE) or calculation (use SPREADSHEET). Authoring guide: a scene is { shapes: [{id,type,x,y,w,h,text?,style?}], edges: [{id,from,to,label?}] } — shapes are the nodes of a lightweight diagram (flow diagrams, brainstorming, journey maps), edges connect them by id. Meaning must live in shape/edge TEXT (text/label) — that is what gets indexed into the knowledge graph; x/y/w/h and style are visual-only layout. Read the board first (rootr_read_whiteboard) before updating so you know the existing shape ids edges refer to.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
iconNoEmoji icon for the node
nameNoWhiteboard name/title
sceneNoInitial scene; defaults to an empty board
configNoFree-form whiteboard config object
parentIdNoParent folder/node id to create it under
workspaceNoWorkspace id; defaults to ROOTR_WORKSPACE/config if omitted
Behavior5/5

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

Describes creation behavior, scene structure, and critical detail that 'text/label' is indexed into the knowledge graph while layout is visual-only. Annotations are minimal but not contradicted.

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 concise (6-7 sentences) and well-structured, front-loading purpose and usage then detailing the scene. No unnecessary words.

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?

Covers purpose, scene structure, and knowledge graph implications well. However, lacks information about the return value (e.g., node ID) since no output schema is provided. Otherwise complete for a create tool.

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?

Schema coverage is 100%, but the description adds significant value by explaining the scene structure (shapes and edges), the role of text/label for indexing, and that defaults apply. This goes beyond the 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 'Create a new WHITEBOARD node (a freeform visual canvas)', providing a specific verb and resource. It distinguishes from DATABASE and SPREADSHEET, and the title aligns perfectly.

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?

Explicitly states when to use 'for flow diagrams, brainstorming, journey maps' and when not 'not for anything that needs typed/trackable rows (use DATABASE) or calculation (use SPREADSHEET)'. Also advises reading before updating, providing clear context.

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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