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set_pick_status

Set pick flags for photos in Lightroom Classic to reject (-1), unflag (0), or pick (1) for organizing your photo catalog.

Instructions

Set pick flag: -1 reject, 0 unflag, 1 pick.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
local_idsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler for the 'set_pick_status' tool, which validates the pick status and sends a 'metadata.set_pick_status' command to the Lightroom bridge.
    async def set_pick_status(status: int, local_ids: list[int] | None = None) -> dict[str, Any]:
        """Set pick flag: -1 reject, 0 unflag, 1 pick."""
        payload = {
            "status": validate_pick_status(status),
        }
        ids = validate_local_ids(local_ids)
        if ids:
            payload["local_ids"] = ids
        return await _call("metadata.set_pick_status", payload)
Behavior1/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states what the tool does at a surface level, without mentioning whether this is a destructive operation, what permissions are required, whether changes are reversible, or how it affects the system state. For a tool that modifies data, this is a significant transparency gap.

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 extremely concise - a single sentence that communicates the core functionality efficiently. Every word earns its place, with no redundant information. The structure is front-loaded with the main action and immediately follows with the parameter semantics.

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 that there's an output schema (which handles return values) and the description provides essential parameter semantics missing from the input schema, the description is adequate for basic usage. However, for a mutation tool with no annotations, it should ideally include more behavioral context about side effects, permissions, or system impact.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides crucial semantic meaning for the 'status' parameter that the schema (with 0% description coverage) completely lacks. It explains that -1 means 'reject', 0 means 'unflag', and 1 means 'pick'. This transforms an ambiguous integer parameter into meaningful business logic. The description doesn't address the 'local_ids' parameter, but the value added for 'status' is substantial.

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 ('Set pick flag') and specifies the three possible values (-1, 0, 1) with their meanings (reject, unflag, pick). It distinguishes this tool from sibling tools like 'set_rating' or 'set_label' by focusing specifically on pick status. However, it doesn't explicitly mention what resource this applies to (presumably photos).

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 'set_rating' or 'set_label'. It doesn't mention prerequisites, context requirements, or any 'when-not-to-use' scenarios. The user must infer usage from the parameter values alone.

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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