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Energi Data Dk

by io.github.pipeworx-io
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Spot Prices

spot_prices
Read-onlyIdempotent

Day-ahead electricity spot prices from Energi Data Service (Energinet, Denmark/Nordic). Prices per bidding zone (PriceArea) in DKK and EUR per MWh, hourly. Bidding zones: DK1 (west Denmark), DK2 (east Denmark), DE (Germany), NO2, SE3, SE4, and others. Omit "area" to get all zones. Keyless official open data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoISO date/time upper bound.
areaNoBidding zone, e.g. "DK1", "DK2", "DE". Omit for all areas.
limitNoMax records (default 24, i.e. last 24 hourly rows).
startNoISO date/time lower bound, e.g. "2026-06-01" or "2026-06-01T00:00".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "area": "DK1",
+    "limit": 24
+  },
+  {
+    "end": "2026-06-02",
+    "start": "2026-06-01"
+  }
+]
  2. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds that the data is 'Keyless official open data', but does not disclose rate limits or pagination behavior, relying on 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?

Three sentences, front-loaded with main purpose, no fluff. Efficiently conveys essential information.

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?

With four well-described parameters and rich annotations, the description provides sufficient context for using the tool. No output schema, but the response is simple hourly prices, so no additional explanation needed.

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% with each parameter described. The description adds useful context about omitting 'area' for all zones and the default limit behavior, enhancing understanding beyond the schema.

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 states it retrieves day-ahead electricity spot prices from Energi Data Service, specifying bidding zones, currencies, and hourly granularity, which distinguishes it from sibling tools like co2_intensity or query_dataset.

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?

Provides examples and mentions options like area and limit, but does not explicitly guide when to use this tool vs siblings. The context is clear but lacks explicit exclusion criteria.

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

All Energi Data Dk toolsInspect
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