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search_metadata

Find photos and videos by metadata criteria such as city, camera model, date range, or favorites. Use when you know specific EXIF fields to filter your library.

Instructions

Search assets by EXIF metadata fields. Use this when you know specific criteria like city, camera model, or date range. For natural language visual queries (e.g. 'sunset at the beach'), use search_smart instead. For browsing without criteria, use list_assets. Read-only.

Args:
    city: City name from EXIF GPS reverse-geocoding (case-sensitive, e.g. 'Barcelona').
    state: State or region name.
    country: Country name (e.g. 'Spain', 'Egypt').
    make: Camera manufacturer (e.g. 'Apple', 'Canon', 'Sony').
    model: Camera model string (e.g. 'iPhone 14 Pro', 'EOS R5').
    taken_after: ISO date — return only assets captured after this date.
    taken_before: ISO date — return only assets captured before this date.
    is_favorite: If true, only return favorites.
    asset_type: 'IMAGE' or 'VIDEO'. Omit for both.
    page: Page number, starting from 1 (default 1).
    size: Results per page (1-200, default 50).

Returns: JSON with total match count, current page, and assets array with IDs, filenames, and dates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo
stateNo
countryNo
makeNo
modelNo
taken_afterNo
taken_beforeNo
is_favoriteNo
asset_typeNo
pageNo
sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Declares 'Read-only' and describes return structure (total count, page, assets with IDs, filenames, dates). No annotations provided, so description effectively carries the burden.

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?

Well-structured with front-loaded purpose, guidelines, parameter details, and returns. Slightly verbose but every sentence adds value.

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?

Covers tool use, parameter meanings, and return format. With 11 params, no required, and output schema mentioned, description is comprehensive enough.

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 has 0% description coverage, but description explains all 11 parameters with examples (e.g., 'Barcelona', 'Apple', 'EOS R5'), hints (ISO date), and defaults (page=1, size=50).

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 'Search assets by EXIF metadata fields', specifying verb and resource. It distinguishes from siblings like 'search_smart' (natural language) and 'list_assets' (browsing).

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 tells when to use ('know specific criteria like city, camera model, or date range') and when not ('for natural language... use search_smart', 'for browsing... use list_assets').

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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