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search_statistics

Count assets in your photo library matching filters like place, date, camera, or favorite status—returning just the total number instead of loading full results.

Instructions

Count how many assets match a filter WITHOUT fetching them. Use this instead of search_metadata whenever only the number matters ('how many photos from Spain?', 'how many did I take in 2019?') — it costs one integer instead of pages of assets. Read-only.

Args:
    city: Count assets from this city.
    country: Count assets from this country.
    state: Count assets from this state/region.
    make: Count assets from this camera make.
    model: Count assets from this camera model.
    is_favorite: If true, count only favorites.
    ocr: Count assets whose recognized text matches (needs OCR on the server).
    created_after: ISO date lower bound on upload date (when it reached Immich).
    created_before: ISO date upper bound on upload date.
    taken_after: ISO date lower bound on capture date (when the photo was taken).
    taken_before: ISO date upper bound on capture date.

Returns: JSON {total}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ocrNo
cityNo
makeNo
modelNo
stateNo
countryNo
is_favoriteNo
taken_afterNo
taken_beforeNo
created_afterNo
created_beforeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A5/5.0
Behavior5/5

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 clearly states 'Read-only,' 'WITHOUT fetching them,' and highlights the efficiency benefit of returning one integer instead of pages of assets. It also notes the OCR server prerequisite, which is useful behavioral context.

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 main purpose and usage guidance are front-loaded in the first sentence, followed by a compact and necessary Args list. Every sentence earns its place, and the examples clarify usage without adding fluff.

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 11 parameters, no annotations, and no visible output schema details, the description covers everything needed: purpose, alternative tool, parameter semantics, return shape ({total}), and behavior. There are no significant gaps for an agent to invoke and interpret this tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must fully document parameters. It provides a meaningful one-line explanation for all 11 parameters, including critical distinctions such as created_after (upload date when it reached Immich) vs taken_after (capture date when the photo was taken). This goes well beyond the bare 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 states a specific verb and resource: 'Count how many assets match a filter WITHOUT fetching them.' It also explicitly differentiates from search_metadata, making it clear this tool returns a count rather than asset pages.

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?

It explicitly says to use this instead of search_metadata whenever only the number matters, with concrete natural-language examples like 'how many photos from Spain?' This provides a clear when-to-use condition and names the alternative.

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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