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places_search_text

Search for places using natural language queries with filters for type, ratings, price, open status, and location.

Instructions

Search for places using natural language queries with advanced filtering options. Supports place type filtering, rating thresholds, price levels, location biasing, and real-time availability status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesText search query for places. Examples: "pizza near me", "Italian restaurants in Rome", "gas stations", "Starbucks in Seattle"
regionNoRegion code for biasing results (ISO 3166-1 alpha-2, e.g., "US", "GB", "DE")
languageNoLanguage code for results (ISO 639-1, e.g., "en", "es", "fr")
open_nowNoFilter for places open now
min_ratingNoMinimum rating filter (1.0-5.0). Example: 4.0 for highly rated places only
max_resultsNo
price_levelsNoPrice levels to filter by (0=Free, 1=Inexpensive, 2=Moderate, 3=Expensive, 4=Very Expensive). Example: [1, 2] for inexpensive to moderate
location_biasNo
excluded_typesNoPlace types to exclude
included_typesNoPlace types to include
rank_preferenceNoHow to rank the results
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not disclose what the tool returns, any pagination, limits, or side effects. Mentions filters but lacks operational details like rate limits or prerequisites.

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 two sentences long, front-loaded with the core action, and contains no redundant information. Every phrase contributes to understanding the tool's purpose and capabilities.

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

Completeness2/5

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

Given the complexity (11 parameters, nested objects, no output schema), the description is insufficient. It does not explain return format, pagination, or any operational constraints, leaving significant gaps for effective use.

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 82%, so the schema already documents most parameters. The description adds value by summarizing filter categories (rating, price, location) but does not provide new per-parameter meaning beyond what the schema offers.

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 tool searches for places using natural language queries with filtering options, which distinguishes it from sibling tools like 'places_nearby' which are location-based. The verb 'search' and resource 'places' are specific.

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 implies use for text-based queries but does not explicitly contrast with sibling tools like 'places_nearby' or 'places_autocomplete'. No guidance on when not to use or alternatives is provided.

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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