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Rootr MCP Server

Create a Rootr spreadsheet

rootr_create_spreadsheet

Create a grid-based spreadsheet node with formulas for budgets, models, and estimates in a Rootr workspace. Cells use A1-style addressing for values and formulas.

Instructions

Create a new SPREADSHEET node (a grid with formulas) in a Rootr (루터) workspace. Use SPREADSHEET when content needs calculation (budgets, models, estimates) — for plain tracked lists use DATABASE instead. Defaults to a single empty "Sheet1" if no data is given. Cells are addressed A1-style ("A1", "B12", ...) in a sparse map: { "A1": { v: 42 }, "B1": { f: "=A1*2" } }. Set a cell to null to clear it. Read the sheet first (rootr_read_spreadsheet) so you know current dimensions and existing content before patching — patchCells only touches the keys you send, everything else is untouched.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoInitial data payload; defaults to a single empty "Sheet1"
iconNoEmoji icon for the node
nameNoSpreadsheet name/title
configNoFree-form spreadsheet config object
parentIdNoParent folder/node id to create it under
workspaceNoWorkspace id; defaults to ROOTR_WORKSPACE/config if omitted
Behavior4/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds valuable context: defaults to a single empty 'Sheet1', cell addressing details, and the effect of setting a cell to null. This goes beyond what annotations provide.

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 front-loaded with the primary action and is well-structured. Each sentence conveys necessary information without redundancy. Slightly long but still efficient.

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?

Given 6 parameters (0 required) and no output schema, the description does not mention what the tool returns (e.g., created node). It provides good workflow context (recommending read first), but the lack of return information is a notable gap.

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%, but the description adds meaning: explains the default when 'data' is omitted, describes the cell address format and sparse map structure, and clarifies how to clear cells. This enriches understanding beyond the schema.

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 SPREADSHEET node' with a specific verb and resource. It distinguishes from DATABASE, making the tool's purpose unambiguous.

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 advises when to use this tool ('when content needs calculation') and when to use an alternative ('for plain tracked lists use DATABASE instead'). Also recommends reading the sheet first before patching.

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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