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immich_describe_photo

Fetch a photo and its metadata into LLM context to generate descriptions, analyze content, or identify what's in the image.

Instructions

Fetch a photo so the LLM can see it, along with all metadata. Perfect for generating descriptions, analyzing content, or identifying what's in a photo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesAsset ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It usefully discloses that the return payload includes both the image content and all metadata, but says nothing about permissions, whether the fetch is read-only vs. destructive, rate limits, or error behavior on an invalid ID.

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?

Two tight sentences with the core action front-loaded. The second sentence leans slightly promotional ('Perfect for...') but still conveys actionable use cases rather than padding.

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 no output schema, the description compensates by stating what comes back (image plus all metadata), which is the key missing structured information. It is nearly complete, with only sibling disambiguation left unaddressed.

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

Parameters3/5

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

Schema description coverage is 100% for the single 'id' parameter, so the schema already documents it fully. The description adds no format, source, or acquisition guidance for the asset ID beyond what the schema provides, making 3 the correct baseline.

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?

States a specific verb and resource (fetch a photo) and adds the distinguishing detail that the image itself is returned for LLM vision, plus its metadata. It does not, however, differentiate itself from close siblings like immich_get_asset or immich_get_asset_info, which an agent could plausibly confuse it with.

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

Usage Guidelines3/5

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

The clause 'Perfect for generating descriptions, analyzing content, or identifying what's in a photo' implies usage contexts, but there is no explicit when-to-use versus immich_get_asset, immich_get_asset_info, or the search_* tools. Usage is suggested rather than routed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.