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Elexon

by io.github.pipeworx-io
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Generation By Fuel

generation_by_fuel
Read-onlyIdempotent

Great Britain half-hourly electricity generation by fuel type (Elexon BMRS FUELHH dataset). Returns MW generated per fuel (CCGT/gas, COAL, NUCLEAR, WIND, BIOMASS, NPSHYD hydro, PS pumped-storage, OCGT, OIL, and interconnector flows INTFR/INTIRL/etc) for each half-hour settlement period. Keyless. 48 settlement periods per day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesPublish-time end, ISO datetime, e.g. "2024-06-01T01:00Z".
fromYesPublish-time start, ISO datetime, e.g. "2024-06-01T00:00Z".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "from": "2024-06-01T00:00Z",
+    "to": "2024-06-01T01:00Z"
+  },
+  {
+    "from": "2024-06-15T12:00Z",
+    "to": "2024-06-15T18:00Z"
+  }
+]
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already convey readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds that the data is keyless and covers 48 periods per day, which is useful but not substantial beyond annotations.

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 description is a single concise paragraph that front-loads the core purpose, listing details efficiently without extraneous words. Every sentence adds value.

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?

Despite no output schema, the description indicates the return format (MW per fuel type) and lists fuels, which is sufficient for a simple read-only data retrieval tool. Input schema fully covers parameters. Annotations handle behavioral context.

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 both parameters. The description adds no additional meaning beyond the schema, meeting the baseline for high coverage.

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 clearly specifies the tool returns 'Great Britain half-hourly electricity generation by fuel type', names the dataset (Elexon BMRS FUELHH), lists fuel categories, and clarifies keyless structure with 48 settlement periods per day, distinguishing it from siblings like 'system_demand'.

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 description explains what the tool does but provides no explicit guidance on when to use it versus alternatives such as 'system_demand' or 'query_dataset'. Usage context is implied but not directly 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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