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Get asset faces

get_asset_faces
Read-only

Retrieves all detected faces in a specified photo, including person assignments and face IDs, to identify who appears or to get IDs for reassigning faces. Read-only.

Instructions

Get all detected faces in a photo with their person assignments. Use this to see who is in a specific photo or to find face IDs for reassign_face. Read-only.

Args:
    asset_id: The asset's UUID.

Returns: JSON array of face detections (each with face_id, person_id, person_name, bounding box).

Input Schema

NameRequiredDescriptionDefault
asset_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.2.1

TDQS

A4.1/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and destructiveHint=false, and the description's 'Read-only' line restates that rather than adding to it. The only extra behavioral context is that results carry person assignments already resolved, which is mildly useful; there is no mention of error behavior for a missing asset or result ordering.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and routing are front-loaded in the first two sentences, which is the right ordering. The Args and Returns blocks are slightly redundant given a full output schema exists, but they are short and not padded.

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

Completeness4/5

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

For a single-parameter read tool with an output schema, the definition covers what it returns at a high level and how to use the result. The only gap is that the return summary partly duplicates the output schema instead of adding interpretation, such as what an empty array means (no faces detected vs. detection not run).

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 description coverage is 0%, so the description carries the burden, and it does clarify that asset_id is 'The asset's UUID' — the format hint is genuinely beyond the bare schema. It does not address lookup failure or whether the ID must come from a prior call such as search or list_assets.

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?

The description states a specific verb and resource ('Get all detected faces in a photo') plus the payload content ('with their person assignments'). It is clearly distinguishable from siblings like list_people or search_people, which operate across the library rather than on one asset.

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

Usage Guidelines4/5

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

It gives two concrete use cases ('see who is in a specific photo', 'find face IDs for reassign_face'), which explicitly routes the agent to the correct follow-up tool. It lacks an explicit when-not statement (e.g., use list_people for a library-wide view), so it falls short of the top mark.

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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