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mcp-edf

mcp-edf

by mgcrea
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

EDF: Compare Years

edf_compare_years
Read-only

Compare each month's electricity or gas consumption against the same month of the previous year, returning kWh, euros and percentage change to reveal how usage and cost shifted.

Instructions

Each month of a year against the same month of the year before, from EDF's own comparison: kWh and euros both years and the change in %, for electricity or gas. total_complete_months sums only months present in both years. EDF rounds to whole kWh and euros. These are raw figures, NOT weather-adjusted: pair them with edf_get_weather (step=month) to tell a colder winter from a change in the home, or use edf_compare_periods for EDF's weather verdict on electricity.

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": {
      "energy": "<energy>"
    },
    "name": "edf_compare_years"
  }
}

Input Schema

NameRequiredDescriptionDefault
yearNoThe year to compare with the one before, e.g. 2026. Defaults to the current year.
energyYesWhich meter to compare.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, it discloses that figures are raw and NOT weather-adjusted, that EDF rounds to whole kWh and euros, and that total_complete_months only sums months present in both years. These are exactly the behavioral caveats that would otherwise cause a misreading of the numbers.

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?

The return shape is front-loaded in the first sentence, followed by the completeness caveat, the rounding rule, and the alternatives routing. Every sentence carries distinct information; nothing is padding.

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

Completeness5/5

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 must describe returns itself, and it does: kWh and euros per year-month, the percent change, and the total_complete_months field. Specifying those fields is reasonably complete for a tool with only two parameters, so it is not missing anything an agent needs.

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?

Schema coverage is 100%, so the year and energy parameters are already documented in the schema. The description still adds interpretive value by clarifying that partial years are truncated via total_complete_months, which tells the agent how the year parameter interacts with completeness, though it adds nothing new about the energy enum.

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?

The description names the exact resource and comparison shape: each month of a year against the same month of the prior year, returning kWh and euros for both years plus the percent change, for electricity or gas. That is specific enough to separate it from period-comparison and raw-consumption siblings without opening any schema.

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

Usage Guidelines5/5

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

It gives explicit routing: pair with edf_get_weather (step=month) when the question is whether a colder winter or a home change explains a delta, and use edf_compare_periods when EDF's own weather verdict is wanted. When-to-use and when-to-use-something-else are both stated.

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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