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mikeysrecipes

TeslaMate MCP Server

get_unusual_power_consumption

Identify unusual power consumption for each Tesla car to detect anomalies or inefficiencies that may indicate problems.

Instructions

Get the unusual power consumption for each car.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the purpose and does not explain what constitutes 'unusual', the time window or aggregation logic, the units, or any assumptions about the returned values. Has output schema partially mitigates this, but the description itself is behaviorally opaque.

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?

The description is a single, clear sentence with no filler. It is appropriately short for a parameterless tool, though adding a brief definition of 'unusual' would improve clarity without sacrificing conciseness.

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?

For a zero-parameter read operation with an output schema, the description is minimally viable. However, it lacks any definition of what makes power consumption 'unusual' and does not clarify how this tool differs from related efficiency metrics, leaving some ambiguity for an agent choosing among siblings.

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?

The tool has zero parameters, so the description gains full marks for not needing to explain parameter semantics. The baseline of 4 applies because there are no parameter details to add.

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?

The description uses a specific verb ('Get') and names the exact resource ('unusual power consumption for each car'). It clearly distinguishes itself from sibling tools focused on efficiency or battery summaries, although the term 'unusual' is undefined.

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 intended use is implied: call this when you need unusual power consumption data per car. There are no explicit when-to-use or when-not-to-use instructions, and no alternative tools are mentioned, but the tool name and description make the basic use case obvious.

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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