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AskMyEV

by com.askmyev
OverviewDiscussionsAdmin

History

get_history
Read-only

Logged history for one metric over a time range, optionally averaged per hour/day/week. Answers from the saved log only; never contacts the car.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "metric": "<metric>"
    },
    "name": "get_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoISO date/time end (default now)
vinNoVehicle VIN (full, or its last 4-6 characters). Required when the account has more than one car (call list_vehicles first and ask the user which car). Optional with one car. Every car on the owner's Tesla account is covered by the plan.
fromNoISO date/time start (default 30 days ago)
metricYes
resolutionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare read-only, closed-world and non-destructive, so the safety profile is covered. The description contributes genuinely new behavior: the data source is the saved log only and the vehicle is never contacted, which tells the agent responses are historical and should not be treated as live telemetry.

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?

Two short sentences, front-loaded with the purpose and followed immediately by the most important behavioral constraint. No filler or redundant restatement of the schema.

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

Completeness3/5

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

There is no output schema, so the description should say what a history result looks like (timestamped points, aggregation buckets, empty ranges), and it does not. It covers data source and aggregation semantics but leaves return shape and default resolution unaddressed.

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 60%: to/from/vin are documented in the schema, while metric and resolution enums have no per-value descriptions. The description's 'averaged per hour/day/week' clarifies what the resolution values mean, but it says nothing about defaults or the VIN multi-car requirement, which the schema does cover.

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+resource ('Logged history for one metric over a time range') and adds the aggregation scope ('averaged per hour/day/week'). It does not explicitly differentiate from overlapping siblings like battery_trend or tire_pressure_trend, so it stops short of a 5.

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?

'Answers from the saved log only; never contacts the car' implicitly tells the agent to use this for historical rather than live data, which rules out get_vehicle_status for the same question. However, no sibling is named and there is no guidance on when to prefer battery_trend or tire_pressure_trend over this tool.

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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