Skip to main content
Glama
rozetyp

emission-factors MCP server

cleanest_hours

Read-only

Find the contiguous N-hour window that minimizes carbon emissions to run flexible loads like EV charging at a US ZIP or balancing authority. Ranks hours using last 7 days of grid carbon data.

Instructions

Find the cleanest (lowest grid carbon) contiguous window of N hours in the day to run a flexible load (batch jobs, EV charging, pumping, HVAC pre-cooling) at a US ZIP code or balancing authority. Based on the hour-of-day pattern of the last 7 days (168 hours) of EIA-930 data, in local time. Returns the cleanest and dirtiest windows, % saved vs the daily average, and all hours ranked. A scheduling guide from recent history, not a forecast.

Input Schema

NameRequiredDescriptionDefault
baNoBalancing authority code (e.g. CISO, ERCO, PJM, MISO, NYIS). Use this OR zip.
zipNo5-digit US ZIP code (or use ba)
durationNoWindow length in hours (default 4)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.7.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only declare readOnlyHint, so the description carries the rest and does so well: data source (EIA-930, last 7 days / 168 hours), local-time basis, and the return contents (cleanest and dirtiest windows, % saved vs daily average, all hours ranked). It doesn't discuss caveats like data lag or coverage gaps, keeping it from a 5.

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?

Three dense sentences that are front-loaded with the purpose, then the data basis, then the return values. Every clause earns its place, and the 'not a forecast' caveat is placed last for emphasis without padding.

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?

With no output schema, the description usefully sketches the return shape (cleanest/dirtiest windows, % saved, ranked hours), and the annotations cover the safety profile. It is essentially complete, though exact field names and units remain unstated.

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 description coverage is 100%, so the schema already documents ba, zip, and duration (including default 4 and the 1–12 range). The description only restates 'N hours' and the ZIP/BA target, adding little beyond what the structured fields provide. Baseline 3 is appropriate.

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?

States a specific verb ('Find') and a precisely scoped resource: the lowest-carbon contiguous N-hour window for flexible loads at a ZIP or balancing authority. This distinguishes it clearly from siblings like hourly_intensity (raw hourly data) and the emissions calculators.

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

Usage Guidelines4/5

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

Gives concrete usage context (batch jobs, EV charging, pumping, HVAC pre-cooling) and an explicit when-not clause: 'A scheduling guide from recent history, not a forecast.' It does not name alternative sibling tools, so it stops short of a 5.

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