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Blyawon

tokensStudioMCP

by Blyawon

node_action

Perform structural actions on Figma nodes including deletion, cloning, selection, zoom, grouping, component conversion, variant combination, appending, and grid arrangement.

Instructions

Run a structural action on nodes (by nodeIds / nodeId / current selection): delete, clone (with offset), select (+scroll into view), zoom, group, to-component (convert each node to a component), combine-variants (promote frames to components and combine into a component set — name them 'Prop=Value' first), append (move into parentId), or arrange (grid-layout the targets with gap/columns).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gapNoGrid gap for 'arrange' (default 40).
nameNoName for group / component set.
actionYes
nodeIdNo
offsetNoClone offset in px (default 20).
columnsNoGrid columns for 'arrange'.
nodeIdsNo
parentIdNoTarget parent for 'append'.
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosure. It details specific behaviors for each action (e.g., clone offset, select scroll into view, combine-variants naming requirement). It also mentions default values for gap and offset. However, it does not explicitly state that delete is destructive or discuss permissions/error states.

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 a single sentence that efficiently covers all actions and input methods. It is front-loaded with the verb and main purpose. While it is dense, there is no extraneous information, making it concise but slightly harder to parse due to length.

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 the complexity (8 parameters, no output schema), the description covers the main actions and their parameters. However, it lacks details on return values, error handling, prerequisites (e.g., selected nodes), and behavior when no nodes are specified. These gaps reduce completeness for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 63%. The description adds context on how parameters like nodeId and nodeIds are used (by ID or current selection) and explains action-specific parameters (e.g., parentId for append). However, it does not add significant detail beyond the schema's descriptions; the baseline of 3 is appropriate.

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 runs structural actions on nodes and enumerates all 9 actions (delete, clone, etc.). It specifies the input methods (by nodeIds, nodeId, or current selection), making the purpose unambiguous. This distinguishes it from sibling tools like create_node or delete_token, which focus on different operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives. It neither states when not to use it nor mentions sibling tools. The user must infer usage from the listed actions, but no exclusion criteria or context-based recommendations are given.

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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