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explore

Read-onlyIdempotent

BROWSING / DISCOVERY search — cities, neighbourhoods, or mixed venues near a location. Use this when the user is exploring a REGION rather than looking for a specific category. Supports population filtering ('cities > 100k'), distance/population sorting, and layer filtering (locality / neighbourhood / venue / address / street). For specific POI categories (gas, food, charging, etc.), use search_places instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude of center point
lonNoLongitude of center point
sizeNoMax results (default 10, max 50)
sortNoSort mode (default: combined)
layersNoComma-separated: venue, address, street, locality, neighbourhood (default: locality)
radiusNoSearch radius with unit, e.g. '50km', '30mi' (default: 150km, max: 500km / ~310mi). Larger radii return 400 INVALID_QUERY.
locationNoCenter point address or 'lat,lon'
min_populationNoMinimum population filter for locality results
boundary_countryNoISO country code to restrict results (alpha-2 or alpha-3)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsNo
geojsonNo
metricsNo
summaryNoMap of scalar facts the LLM should surface verbatim
display_hintNo

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint), the description adds significant behavioral context: it mentions population filtering, sorting modes, layer filtering, and even warns that larger radii return 400 INVALID_QUERY. This extra detail about error conditions and customization goes beyond what annotations provide.

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 concise (3 sentences) and front-loaded with the primary purpose. It packs in usage guidance, feature highlights, and an alternative tool without unnecessary filler. Every sentence contributes meaning.

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?

For a tool with 9 parameters, an output schema, and a rich set of features, the description is remarkably complete. It covers the core purpose, when to use it, key capabilities, limitations (radius error), and alternatives. The output schema exists, so return values need not be described. This is a fully self-sufficient description.

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

Parameters4/5

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

The schema already documents all 9 parameters with descriptions (100% coverage), so the baseline is 3. The description adds functional context by explaining how parameters like population filtering, sorting, and layers work together (e.g., 'cities > 100k' implies min_population). This adds value beyond the schema, hence a 4.

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 identifies the tool as a browsing/discovery search for cities, neighbourhoods, or mixed venues near a location. It distinguishes itself from sibling tools by explicitly stating it is for exploring a region rather than a specific category, and names search_places as the alternative for specific POI categories.

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 provides explicit guidance on when to use this tool ('when the user is exploring a REGION rather than looking for a specific category') and names an alternative tool (search_places) for different use cases. This is clear, actionable guidance.

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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TDQS

A4.4/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose. Overlapping tools (geocode vs geocode_structured, explore vs search_places, map_match vs trace_attributes) are explicitly differentiated in their descriptions, with cross-references guiding correct selection. No two tools appear to do the same thing.

Naming Consistency4/5

Most tools follow a predictable verb_noun pattern (geocode, reverse_geocode, batch_geocode, search_places, resolve_intersection), but there are minor deviations: some tools use noun-only names (directions, traffic, weather) and a couple use noun_verb order (place_get, geofence_contains). This creates slight inconsistency but remains readable.

Tool Count4/5

At 19 tools, the set is slightly heavy but each tool earns its place by covering a distinct geospatial function. The breadth spans geocoding, routing, places, telematics, geofencing, traffic, weather, and account management, making the count reasonable for a comprehensive geo API.

Completeness5/5

The tool surface is remarkably complete for a geospatial server: forward, reverse, batch, structured, and intersection geocoding; routing, matrix, and isochrones; place search, exploration, and ID lookup; map matching, trace attributes, and point snapping; plus geofencing, traffic, weather, and quota management. No critical gaps or dead ends apparent.

Resources