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sweetrb

apple-photos-mcp

by sweetrb

list-persons

Lists all named people identified by Photos face recognition, sorted by number of photos. Use to discover person names before filtering photos by person.

Instructions

Use when: you want the catalog of named people from Photos face recognition — e.g. to discover exact person names before filtering query by person, or to see who appears most. Pass limit for the top-N; unidentified faces appear as UNKNOWN. Returns: persons with their photo counts, sorted most-photographed first. Do not use when: you want photos of a person — use query with the person filter; or you want subject tags rather than people — use list-keywords.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoTop-N persons
libraryNoPath to a .photoslibrary (default: system Photos library)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
personsNo
Behavior4/5

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

Describes output format (persons with photo counts, sorted most-photographed first), handling of unidentified faces as _UNKNOWN_, and limit behavior. Lacks explicit read-only or permission disclosure, but behavior is well covered for a list 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?

Concise 5-line description, front-loaded with usage conditions, no redundant text. Every sentence adds information.

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

Completeness5/5

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

Given output schema exists, description completes the picture with return format and usage context. Covers edge cases like _UNKNOWN_ and limits.

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?

Schema covers both parameters with descriptions, but description adds context: limit for top-N and default library path. Adds value beyond schema.

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?

Description clearly states 'catalog of named people from Photos face recognition' and distinguishes from sibling tools like query (for photos of a person) and list-keywords (for subject tags).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly provides 'Use when' and 'Do not use when' sections with alternative tools, such as using query with person filter for photos of a person.

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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