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Get Operating Reserve Prices

get_operating_reserve_prices
Read-onlyIdempotent

Returns daily operating reserve price components and volumes by reserve type and time block. Maintains distinct active, standby, activation, and blended clearing prices.

Instructions

Returns daily active and standby operating-reserve price components and volumes by regulating, spinning, or supplemental product and time block. Active price, standby premium, activation strike, and clearing blended price remain distinct.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYesPagination state for a stable in-memory report result.
metadataYesProvenance and semantic metadata attached to dataset responses.
warningsNo
intervalsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behaviors, so the bar is lower. The description adds useful interpretive context: that active price, standby premium, activation strike, and clearing blended price remain distinct. This prevents an agent from incorrectly aggregating or conflating these components.

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?

Two sentences carry exactly the needed information: the first defines the scope and outputs, the second clarifies an important semantic distinction. There is no wasted wording or repetition of schema details.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema and rich annotations, the description covers the core domain and return semantics, but lacks usage guidance and pagination behavior. It also does not specify allowed date ranges or timezone conventions, which an agent would need for correct invocation. It is adequate but not fully complete.

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 0%, so the description must compensate for parameter documentation. It references the reserve_types enum values ('regulating, spinning, or supplemental') and 'time block' which loosely maps to start_date/end_date and the product dimension. However, it does not explain the request wrapper, limit/offset pagination, or date format, leaving a meaningful gap.

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 states a specific verb ('Returns') and resource ('operating-reserve price components and volumes') and identifies the key dimensions (regulating/spinning/supplemental product, time block, active versus standby). This makes it clearly distinguishable from siblings like get_operating_reserve_activations, get_operating_reserve_forecast, and summarize_operating_reserve_market.

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 explicit guidance about when to use this tool versus alternatives. The description implies it is for daily reserve price data, but it does not mention exclusions, preferred scenarios, or sibling tools. An agent would have to infer usage from the resource name and content.

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