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Vangrid coverage query

vangrid_coverage_query

Query anchored ground-level captures by area and time window to get geotagged observations with on-chain attestations, enabling verifiable provenance checks.

Instructions

Find anchored ground-level captures inside an area and time window. Each observation carries a coarse location (geohash precision 6), capture time and the EAS attestation on Base that anchors it. Paid per call in USDC on Base (eip155:8453) or Arc mainnet (eip155:5042), about $0.01. Area: GeoJSON Point with radius_m (max 5000) or a Polygon whose bounding box is at most 100 km².

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoISO-8601 end, default now
aoiYesGeoJSON geometry: Point [lng, lat] or Polygon [[[lng, lat], ...]]
fromNoISO-8601 start, default 7 days before "to"
limitNodefault 100
radius_mNoPoint only: radius in metres, default 500

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses paid-per-call pricing in USDC on Base (eip155:8453) or Arc (eip155:5042) at ~$0.01, the coarse geohash-6 location precision, the EAS attestation anchoring, and hard area limits. It omits any note on rate limits or failure modes, which keeps it short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences that are front-loaded on what the tool returns, followed by cost and area constraints. The pricing sentence packs two chains, addresses and a cost figure, but every element is load-bearing for a paid tool, so little is wasted.

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

Completeness4/5

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

With no output schema, the description correctly spends space enumerating return fields (coarse location, capture time, EAS attestation), and it covers payment and area validity. It leaves pagination/limit semantics and error behavior to the schema, which is acceptable for this complexity level.

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 coverage is 100%, so the baseline is 3, but the description adds constraints the schema does not encode: the bbox limit of 100 km² and the max radius of 5000 m tied to Point geometry. It still doesn't clarify defaults for from/to or limit behavior beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Find') and resource ('anchored ground-level captures') bounded by an area and time window, so the agent knows exactly what comes back. It does not name a sibling like vangrid_observation or vangrid_verify_provenance, so differentiation must be inferred from the noun phrase alone.

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 area/time framing implies when the tool is appropriate (spatial coverage inspection), but there is no explicit when-to-use/when-not-to-use guidance and no routing to the sibling tools that fetch a single observation or verify provenance. Usage is left to inference.

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