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pre170

VoltWise MCP Server

by pre170

power_explain_usage_change

Explains household power usage changes by ranking observed contributors and keeping unattributed consumption intact.

Instructions

Rank observed contributors and preserve unattributed household usage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
current_kwhNo
limitationsYes
contributorsYes
unattributed_kwhYes
speakable_summaryYes
household_change_kwhYes
known_contribution_kwhYes
attribution_overage_kwhYes
previous_equivalent_kwhNo
household_change_percentYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, and it discloses only one trait: that unattributed usage is preserved rather than dropped. It says nothing about required inputs, data sources, timeframe assumptions, or how contributors are ranked, which matters for a no-parameter analysis tool.

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?

A single tight sentence with no filler, and the two key behaviors (ranking, preserving unattributed usage) are front-loaded. It is efficient, though the terseness trades away clarity rather than genuinely earning it.

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

Completeness2/5

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, but the description still leaves the tool's purpose and selection context ambiguous against eight power siblings. For a zero-parameter analytical tool with no annotations, this is too thin to guide correct invocation.

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 takes zero parameters, so there is no parameter surface for the description to compensate for. Baseline 4 applies; nothing is misleading about how inputs are described.

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

Purpose3/5

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

The description gestures at the tool's job — ranking contributors to a usage change and retaining unattributed household usage — but never states plainly that it explains why household power usage changed. The resource is inferable from the name, not from the text, and it does not distinguish itself from siblings like power_compare_periods.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no indication of when to call this versus power_compare_periods, power_run_diagnostic, or power_forecast_bill. Usage is only loosely implied by the phrase 'explain usage change'; no prerequisites, triggers, or exclusions are given.

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