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Tesla Trip Cost

tesla_trip_cost

Estimate trip energy use, cost, and range to a destination using your 30-day average efficiency and current battery level. Also compare estimated gas costs.

Instructions

Estimate trip cost to a destination -- kWh, cost, range check.

Uses your personal 30-day average efficiency and current battery level. If QWeather is configured, the current weather at the origin and the destination is shown for reference only — it does NOT change the energy or cost estimate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
car_idNoFilter by vehicle ID (default: TESLA_CAR_ID env or first car)
gas_priceNoGas price per gallon (default from TESLA_GAS_PRICE env)
destinationYesCity, address, or place name (e.g. "Atlanta, GA")
mpg_equivalentNoComparable gas vehicle MPG (default from TESLA_GAS_MPG env)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations the description carries the full burden, and it does disclose meaningful behavior: the estimate derives from a personal 30-day average efficiency and current battery level, and weather is display-only. It omits whether the call is side-effect free, permission/env requirements for the fallback defaults, and failure behavior for un-geocodable destinations.

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 outputs are front-loaded in the first line, followed by methodology and the weather caveat. Every sentence carries information; the weather note is slightly longer than needed but prevents a real misconception, so it earns its place.

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?

An output schema exists, so return values need not be explained, and the description covers purpose, data sources, and a caveat. What is missing is usage routing against the many savings/efficiency siblings, which leaves a modest gap for a tool in this crowded family.

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 100%, so all four parameters (car_id, gas_price, mpg_equivalent, destination) are already documented, including their env-var defaults. The description adds no parameter-level meaning, which is the correct baseline of 3 when the schema does the heavy lifting.

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?

Specific verb (estimate) plus resource (trip cost to a destination) and an enumeration of the outputs (kWh, cost, range check). An agent can distinguish this from compute-only siblings like tesla_efficiency, though it never names the closest alternatives (tesla_savings, calculate_eco_savings_vs_icev).

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?

Usage is implied by the required 'destination' argument and the trip-planning framing, but there is no explicit when-to-use guidance, no prerequisites, and no exclusions naming which sibling to prefer for savings or historical-trip questions. Adequate but with clear gaps.

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