ThinAir Geo

geocode_structured

Read-onlyIdempotent

Geocode from discrete address components (address, locality, region, postalcode, country) instead of one free-text string. Use when the input is already fielded (forms, CRM records, stop tables) — skips free-text parsing so components can't be mis-tokenized. At least one component is required. No cross-street field: for named intersections use resolve_intersection or geocode.

Input Schema

TableJSON Schema

Name	Required	Description
`size`	No	Number of candidates to return (default 5, max 40)
`region`	No	State / province — full name or abbreviation (e.g. 'TX')
`address`	No	Street address — house number + street name (e.g. '1600 Pennsylvania Ave NW')
`country`	No	ISO 3166-1 alpha-2/alpha-3 country code (full names also resolve)
`locality`	No	City / town name
`focus_lat`	No	Bias results near this latitude
`focus_lon`	No	Bias results near this longitude
`postalcode`	No	Postal / ZIP code
`boundary_country`	No	Scope results to this ISO country code — wins over `country` for boundary filtering

Output Schema

TableJSON Schema

Name	Required	Description
`items`	No
`geojson`	No
`metrics`	No
`summary`	No	Map of scalar facts the LLM should surface verbatim
`precision`	No
`display_hint`	No

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds valuable context beyond annotations: 'At least one component is required' and 'No cross-street field' clarifies a functional limitation. It doesn't over-promise or contradict the read-only nature.

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?

Three sentences, each earning its place: the first defines what it does, the second gives use cases and benefit, the third states a constraint and alternatives. No redundancy.

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?

Given a rich output schema and detailed per-parameter descriptions, the tool description fully covers purpose, usage context, constraints, and alternatives. It is complete for an AI agent to select and invoke correctly.

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?

Schema description coverage is 100%, giving each parameter a clear meaning. The description adds the cross-parameter constraint that at least one component is required, which is not encoded in the schema's required list. However, it mostly restates component names already present in the schema.

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 geocodes from discrete address components rather than a free-text string, and explicitly distinguishes it from the sibling geocode and resolve_intersection tools. The verb 'Geocode' plus resource noun is specific and unambiguous.

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?

Provides explicit when-to-use guidance ('Use when the input is already fielded') and an exclusion ('for named intersections use resolve_intersection or geocode'). This directly helps the agent choose among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All ThinAir Geo tools Inspect

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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

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