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evcharging

evcharging
Read-only

EV charging stations (and other alternative fuel stations) near a place in the US and Canada: network, Level 2 and DC fast port counts, connector types, access hours, pricing, address and distance, from the US DOE station locator. Costs $0.005 USDC per call (x402).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNo
lonNo
fuelNoELEC (default), CNG, LPG, E85, HY, BD
nearNoPlace or address
limitNo
networkNoe.g. Tesla, ChargePoint Network
connectorNoJ1772, J1772COMBO, CHADEMO, TESLA
radius_milesNoDefault 5

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely useful non-annotation context: the upstream data source, the US/Canada coverage boundary, the shape of returned data, and critically the $0.005 USDC per-call x402 cost, which affects whether an agent should call it at all.

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?

Purpose and scope are front-loaded in the first clause, and the cost sentence is short and high-value. The middle attribute list is dense but earns its place given there is no output schema; only slight trimming would be possible.

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 eight optional parameters, no output schema, and no enums, the description compensates by enumerating return fields, naming the data source, bounding geography, and disclosing cost. The one meaningful gap is how location input should be supplied (lat/lon vs. near), which matters because nothing is marked required.

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 63%, so the schema documents most parameters. The description names concepts that map loosely to filters (network, connector types, fuel) but frames them as outputs rather than inputs, and it never resolves the key ambiguity of whether lat/lon, near, or both are needed when zero parameters are required. Baseline 3 is appropriate.

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 a specific resource (EV charging stations plus other alternative fuel stations), the geographic scope (US and Canada), and the data source (US DOE station locator). It lists the returned attributes (network, Level 2/DC fast port counts, connectors, hours, pricing, distance), which cleanly separates it from siblings like gas, energy, or places.

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 phrase 'near a place in the US and Canada' implies the usage context and implicitly bounds coverage, but the description never states when to prefer this over adjacent siblings (gas, places, geocode) or any conditions/exclusions. An agent can infer intent but gets no explicit routing 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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