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search_smart

Find photos by typing a natural language description; optionally filter by city, state, country, or date to pinpoint results.

Instructions

AI-powered visual search using CLIP. Describe what you're looking for in natural language (e.g. 'sunset at the beach', 'birthday cake', 'mountain landscape').

Can be combined with location and date filters.

Args:
    query: Natural language description of what to find.
    city: Optional city filter.
    state: Optional state/region filter.
    country: Optional country filter.
    taken_after: ISO date — only photos after this date.
    taken_before: ISO date — only photos before this date.
    page: Page number (default 1).
    size: Results per page (default 50, max 200).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
cityNo
stateNo
countryNo
taken_afterNo
taken_beforeNo
pageNo
sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It describes the tool as AI-powered and filterable, but does not disclose performance characteristics, rate limits, or confirm read-only nature, though the search name implies no side effects.

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 description is brief yet complete, with a two-sentence intro and a bulleted list of parameters. Every sentence adds value with no redundancy.

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?

Given the 8 parameters and lack of annotations, the description covers the main purpose and all parameters adequately. With an output schema present, the lack of output description is acceptable. However, it could briefly mention the nature of results.

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 fully compensates by providing clear explanations for all 8 parameters, including format hints (e.g., 'ISO date') and defaults for page and size.

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 it is an 'AI-powered visual search using CLIP' that accepts natural language queries. It distinguishes from sibling 'search_metadata' by focusing on visual content rather than metadata.

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 description mentions that it can be combined with location and date filters, giving some usage context, but does not explicitly state when to use this tool versus alternatives like 'search_metadata'.

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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