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Lightroom MCP Elite

Lightroom MCP Elite

by baramesh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

set_keywords

Add, remove, or replace keywords on selected photos to keep Lightroom catalog metadata organized. Provide photo IDs and keywords, then choose the desired mode.

Instructions

Add, remove, or replace keywords on specified photos.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "photo_ids": "<photo_ids>",
      "keywords": "<keywords>"
    },
    "name": "set_keywords"
  }
}

Input Schema

NameRequiredDescriptionDefault
modeNoadd
keywordsYes
photo_idsYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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 honestly indicates that the tool mutates keywords in three possible ways (add, remove, replace), which is core behavioral information. However, it does not explain what 'replace' means for existing keywords, whether changes are reversible, or what the response will contain.

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, tightly-worded sentence with no filler or repetition. All three core operations are front-loaded, making the tool's purpose immediately scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with zero annotations and zero schema descriptions, a one-line summary is insufficient. The agent still lacks clarity on how mode values map to behaviors, the semantics of 'replace', and whether existing keywords are overwritten or merged. The presence of an output schema helps return-value understanding but does not fix these gaps.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It provides loose context connecting 'keywords' and 'photos' to the action, but it never explicitly maps the mode parameter to the add/remove/replace operations, nor explains the behavior of photo_ids beyond 'specified photos'. This leaves meaningful ambiguity for a required-by-default mode parameter.

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 ('Add, remove, or replace') and the resource ('keywords on specified photos'), making the tool's function immediately understandable. It doesn't explicitly differentiate from siblings, but the resource is distinct enough that confusion with set_rating or set_develop_settings is unlikely.

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?

No guidance is given about when to use this tool versus alternatives, nor any context about prerequisites or typical workflows. The agent must infer usage solely from the tool name and the brief description.

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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