ThinAir Geo

trace_attributes

Read-onlyIdempotent

Trace attributes return road/network attributes for matched traces. Feed a GPS breadcrumb trail (2–100 points) and get per-segment road names, road classes, speed limits, surfaces, truck-route flags, and segment lengths along the matched route, plus a matcher confidence score. Use to audit what roads a vehicle actually used (speed-limit compliance, truck-route adherence, surface checks). For just the matched route line, use map_match.

Input Schema

TableJSON Schema

Name	Required	Description
`shape`	Yes	Raw GPS breadcrumb trail in travel order — 2 to 100 points of { lat, lon, time? }. `time` is optional epoch seconds; timestamps improve match quality on noisy traces.
`costing`	No	Transport mode the trace was recorded with (default: auto)
`search_radius`	No	Snap radius in meters around each point (1–100). Increase for noisy GPS.
`vehicle_profile`	No	Truck preset (DRY_VAN_53, FLATBED_48, BOX_TRUCK_26, …) — same 10-profile table as directions. Implies costing=truck.

Output Schema

TableJSON Schema

Name	Required	Description
`meta`	No
`edges`	Yes
`admins`	No
`costing`	Yes
`geojson`	No
`matched`	Yes
`geometry`	No
`confidence`	Yes	Matcher confidence 0–1
`edge_count`	Yes
`road_names`	Yes
`distance_km`	Yes
`costing_options`	No
`vehicle_profile`	No
`duration_seconds`	No

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true. The description adds behavioral context by revealing the matcher confidence score and the segment-level output, and the audit use case. No contradictions.

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: function, output/use case, and sibling alternative. Front-loaded with the main verb and resource, no filler.

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?

With a strong output schema and detailed parameter schema, the description covers purpose, use case, and alternatives. It is complete for a read-only trace-analysis tool with good annotations.

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 description coverage is 100%, so baseline is 3. The description doesn't add parameter-specific meaning beyond what the schema already provides; it only summarizes the input (GPS breadcrumb) and output. No new semantics over 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?

States it 'return road/network attributes for matched traces' and lists the concrete attributes (road names, classes, speed limits, etc.). Explicitly distinguishes from sibling `map_match` by saying 'For just the matched route line, use `map_match`'.

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 clear when-to-use context: 'Use to audit what roads a vehicle actually used (speed-limit compliance, truck-route adherence, surface checks)'. Also explicitly names the alternative `map_match` for route-line-only needs.

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

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