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figma-jev-console

by anuragfolio

jev_resolve_pending

Resolve a pending design decision by applying the best guess, rejecting it, choosing element or token scope, sending it to the LLM, or marking it done after manual code changes.

Instructions

Decide a pending item: 'apply' writes the best guess, 'reject' drops it, 'element' / 'token' choose the scope for a design-token color, 'llm' hands it to the LLM, 'done' marks it finished after you changed the code yourself (Figma is then redrawn).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
actionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A3.9/5.0
Behavior4/5

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

The description discloses the behavior of each action: 'apply' writes, 'reject' drops, 'element/token' choose scope, 'llm' hands off, 'done' marks finished and triggers redraw. This is comprehensive for a decision tool, but it doesn't mention side effects like irreversibility or error conditions. Given no annotations, the description carries the full burden and does so adequately.

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 sentence that front-loads the purpose and then lists each action compactly. Every part contributes to understanding, with no fluff.

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?

The description covers all actions and their outcomes. It does not describe return values, but that is likely irrelevant for a decision tool. It doesn't mention prerequisites like whether the item must exist, but that is a minor omission. Overall, it is sufficiently complete.

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 schema has 0% description coverage, so the description must explain the parameters. It does explain the 'action' parameter by detailing each enum value's meaning. However, the 'id' parameter is not explicitly described, though it is implied as the pending item identifier. The description adds value over the schema by clarifying the semantics of the actions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Decide a pending item' and enumerates the actions with their outcomes. It is specific and unambiguous, though it doesn't explicitly differentiate from sibling tools like jev_list_pending, but the purpose is clear.

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

Usage Guidelines3/5

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

It explains when to use each action (e.g., 'apply' when you want to write the best guess), but it doesn't explicitly state when to use this tool versus alternatives. The context of pending items is implied but not contrasted with other tools. It provides no exclusions or alternative references.

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