Skip to main content
Glama
anuragfolio

figma-jev-console

by anuragfolio

jev_execute

Execute custom Figma plugin API code asynchronously inside the Jev Bridge plugin, with figma in scope, and return JSON-serializable values.

Instructions

Escape hatch: run Figma plugin API code inside the Jev Bridge plugin (async function body with figma in scope; return a JSON-serializable value).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It usefully explains that the input is an async function body with `figma` in scope and that the return value must be JSON-serializable, but it does not disclose potential side effects, destructive document changes, error behavior, or permission implications of executing arbitrary code.

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 a single compact sentence that front-loads the core idea ('Escape hatch') and packs all necessary constraints into a small amount of text. Every clause earns its place, with no filler or redundant repetition of the tool name.

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?

For a tool with no output schema, no annotations, and a single undocumented parameter, the description provides the essential invocation contract: input format, execution context, and return serialization. However, it omits error handling semantics, side-effect warnings, and any indication of what happens on invalid or non-serializable returns, leaving noticeable gaps for an arbitrary-code execution tool.

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 input schema only describes `code` as a string with 0% description coverage, so the description must compensate. It does by explaining that the code is an async function body, runs inside the plugin with `figma` available, and must return a JSON-serializable value, which adds meaningful meaning beyond the raw schema type.

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 states a specific action ('run Figma plugin API code') and a specific resource/context ('inside the Jev Bridge plugin'). It also frames itself as an 'escape hatch', which clearly distinguishes it from the more specialized sibling tools by presenting it as the generic fallback for arbitrary code.

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 term 'escape hatch' gives clear contextual guidance that this tool is for cases where the dedicated sibling tools do not apply. It does not explicitly name alternatives or exclude conditions, but the implication is strong enough for an agent to infer when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.