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Illustrator AI & MCP Control

by Bieuulls
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Python
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illustrator_history

Destructive

Undo mistakes, redo actions, and manage named checkpoints to recover previous Illustrator states.

Instructions

Undo or redo actions in Illustrator.

CONTRACT: readOnly=False, destructive=True, idempotent=False, openWorld=False

WHEN TO USE:

  • Reverting mistakes (action='undo', count=N)

  • Restoring undone changes (action='redo')

  • Saving/restoring named checkpoints for recovery

EXAMPLES: Undo three steps: {"params": {"action": "undo", "count": 3}} Save a checkpoint before risky work: {"params": {"action": "checkpoint_save", "name": "before_boolean"}} Restore it: {"params": {"action": "checkpoint_restore", "name": "before_boolean"}} List checkpoints: {"params": {"action": "checkpoint_list"}}

NOTES:

  • Checkpoints capture MCP-managed items only (those with @mcp:id)

  • checkpoint_restore is mutate-in-place; may require multiple undo to revert

  • undo/redo change document state (destructive)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

The CONTRACT line aligns with annotations, and the NOTES add non-obvious behavioral context: checkpoints only cover MCP-managed items, checkpoint_restore is mutate-in-place and may need multiple undo steps, and undo/redo are destructive. This goes beyond what annotations alone reveal.

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?

Well structured with CONTRACT, WHEN TO USE, EXAMPLES, and NOTES. The primary purpose is front-loaded, examples are compact, and each section earns its place without excessive prose.

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 the main invocation patterns for undo, redo, checkpoint save/restore/list, and notes the key risks. The schema supplies the remaining enum and parameter details, including checkpoint_delete. Without an output schema, some return-value expectations are left to the agent, but that is not a significant gap for this 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 schema already documents all five parameters with descriptions, so the baseline is 3. The description adds concrete JSON examples showing valid combinations of action with count and name, which clarifies how to structure calls. It does not elaborate on jobId or expected_document_token, but the schema covers those.

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?

Opens with a specific verb and resource: 'Undo or redo actions in Illustrator,' and the examples extend that to named checkpoints. This clearly distinguishes it from the sibling tools, none of which cover undo/redo or history management.

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?

A dedicated WHEN TO USE section lists concrete scenarios: reverting mistakes, restoring undone changes, and saving/restoring checkpoints. It does not explicitly name alternatives or when not to use the tool, but the guidance is clear enough for an agent to select this tool for history operations.

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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