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datasets_google_map_search

Search and filter stored Google Maps business data using criteria like category, location, rating, and review count. Get sorted results for analysis.

Instructions

Search stored Google Maps businesses. Searches Google Maps business records stored in Elasticsearch. Sort enum: relevance, updated_at_desc, rating_desc, review_count_desc, distance_asc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoExact category filter, max 128 characters
cityNoExact city filter, max 128 characters
countryNoExact country filter, max 128 characters
countyNoExact county filter, max 128 characters
has_phoneNoFilter by phone presence
has_websiteNoFilter by website presence
latNoLatitude for radius filtering or distance sort
lonNoLongitude for radius filtering or distance sort
min_ratingNoMinimum rating, 0 through 5
min_review_countNoMinimum review count
pageNoPage number, defaults to 1
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
qNoFull-text business search query, max 256 characters
radius_mNoRadius in meters, 1 through 50000; requires lat and lon when supplied
sortNoSort enum: relevance, updated_at_desc, rating_desc, review_count_desc, distance_asc
stateNoExact state filter, max 128 characters
townNoExact town filter, max 128 characters
Behavior2/5

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

With no annotations, the description carries full burden. It only states it searches records and lists sort options, but doesn't disclose read-only nature, performance, pagination behavior, or other traits beyond basic functionality.

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?

Two concise sentences that get straight to the point. No redundant information or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 17 optional parameters and no output schema, more context on how the search works and what the response contains would improve completeness. Currently minimal.

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 coverage is 100% with good parameter descriptions. The description only adds the sort enum list, so it adds little value beyond the schema. Baseline 3 is appropriate.

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 searches stored Google Maps businesses in Elasticsearch. It distinguishes from siblings like google_map_search (likely live search) and datasets_google_map_facets (facets).

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?

No explicit guidance on when to use this tool versus alternatives. The description implies it's for stored data, but doesn't contrast with live search or facets. Adequate but could be improved.

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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