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get_capabilities

Check what the Immich server supports first—OCR, smart search, facial recognition, and version-specific quirks—so you only offer features that will work.

Instructions

What this Immich server can do: version, feature flags and known quirks. Use this once at the start of a session to learn whether OCR, smart search or facial recognition are available before offering them, and which behaviours differ between Immich 2.x and 3.x. Read-only.

Returns: JSON with server_version, immich_major, features (the server's own
flags: ocr, smartSearch, facialRecognition, map, trash...) and quirks (plain
sentences about version-specific behaviour the caller should know). When the
API key may not read the feature flags, features is empty and a note says so;
the version and the quirks still come back.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries full responsibility. It discloses that the tool is read-only, describes the degradation behavior when the API key lacks feature-flag access ('features is empty and a note says so; the version and the quirks still come back'), and explains the format of quirks. This is significant behavioral context beyond any schema or annotation, giving the agent realistic expectations of output under permission limitations.

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?

The description is well organized with a front-loaded summary, a usage directive, and a detailed 'Returns:' section. It is slightly longer than the absolute minimum but every sentence carries useful information—none is wasted. The colon-separated list of feature flags is dense but readable.

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?

The description covers the tool's purpose, usage timing, return fields, quirks format, permission degradation, and read-only nature. Given the empty input schema and existing output schema, nothing essential is missing. An agent can invoke it and interpret its output confidently.

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?

The tool has zero parameters, so the baseline of 4 applies. The description does not need to explain parameters because there are none. It focuses on return semantics, which is appropriate given the empty 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?

The description clearly states the resource (server capabilities) and the specific aspects returned: version, feature flags, and known quirks. It goes beyond a simple verb+noun by enumerating the exact features ('OCR, smartSearch, facialRecognition, map, trash') and explicitly separates this tool from get_server_version and ping through scope. An agent can understand what this tool does and what it uniquely provides.

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?

The description gives explicit timing and purpose: 'Use this once at the start of a session to learn whether OCR, smart search or facial recognition are available before offering them.' It also explains when version-specific behavior matters. It does not name alternatives or explicitly say when not to use it, but the context is clear enough for an agent to select it appropriately.

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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