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undo

Reverse the most recent edit in Lightroom Classic to correct mistakes or test adjustments.

Instructions

Undo the last Lightroom operation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The tool named 'undo' is registered as an MCP tool and delegates the request to the Lightroom plugin via `_call("system.undo")`.
    async def undo() -> dict[str, Any]:
        """Undo the last Lightroom operation."""
        return await _call("system.undo")
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but doesn't cover critical aspects like whether it requires specific permissions, if it's reversible (via 'redo'), what happens on failure, or any rate limits. This leaves significant gaps for a mutation tool.

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, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly.

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 tool's complexity (a mutation with no annotations) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks details on behavioral traits like error conditions or dependencies, which are important for safe usage in this context.

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 tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's function, which aligns with the baseline expectation for zero-parameter tools.

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 action ('undo') and the target ('last Lightroom operation'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from its sibling 'redo', which handles redoing operations, though this distinction is implied by the tool names.

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 provides no guidance on when to use this tool versus alternatives, such as 'redo' for reversing an undo or 'reset_current_photo' for more extensive changes. It lacks context on prerequisites like checking 'can_undo' first or any limitations on what operations can be undone.

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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