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rotate_right

Rotate selected photos 90 degrees clockwise in Lightroom Classic to correct orientation or adjust composition for editing workflows.

Instructions

Rotate selected photos 90 degrees right.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
local_idsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function 'rotate_right' which registers the tool and invokes the underlying Lightroom metadata call.
    @mcp.tool()
    async def rotate_right(local_ids: list[int] | None = None) -> dict[str, Any]:
        """Rotate selected photos 90 degrees right."""
        ids = validate_local_ids(local_ids)
        payload: dict[str, Any] = {}
        if ids:
            payload["local_ids"] = ids
        return await _call("metadata.rotate_right", payload)
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the action but doesn't disclose behavioral traits like whether this is a destructive operation (likely yes, as rotation modifies photos), permission requirements, or what happens if no photos are selected. The description adds minimal context beyond the basic action.

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 with zero wasted words. It's front-loaded with the core action and target, 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 has an output schema (which likely describes the result), the description doesn't need to explain return values. However, as a mutation tool with no annotations and incomplete parameter documentation, it should provide more context about side effects, prerequisites, or error conditions to be fully 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?

With 0% schema description coverage and 1 parameter, the description compensates by implying the parameter's purpose: 'selected photos' suggests 'local_ids' refers to photos to rotate. However, it doesn't explain the parameter's format (array of integers vs. null) or default behavior (null likely means use currently selected photos).

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 ('rotate') and target ('selected photos') with specific direction ('90 degrees right'), making the purpose immediately understandable. It distinguishes from the sibling 'rotate_left' by specifying direction, though it doesn't explicitly mention that distinction.

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 like 'rotate_left' or other photo manipulation tools. It doesn't mention prerequisites (e.g., needing photos to be selected first) or contextual constraints.

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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