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Compare Forecast To Actual

compare_forecast_to_actual
Read-onlyIdempotent

Compare Alberta Internal Load forecast with actual values over any time range, returning mean error, MAE, RMSE, MAPE, and paired intervals to assess forecast accuracy.

Instructions

Compares Alberta Internal Load forecast versus actual over [start, end) in MW. Returns mean error, MAE, RMSE, MAPE, and paired intervals. Timestamps are America/Edmonton.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYesCompare Alberta Internal Load forecast versus actual over a range.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rmse_mwNo
metadataYesProvenance and semantic metadata attached to dataset responses.
warningsNo
intervalsNoPaired intervals (may be truncated for large ranges).
mean_error_mwNo
max_abs_error_mwNo
mean_abs_error_mwNo
observation_countYes
mean_abs_pct_errorNo
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false. The description adds concrete output details (mean error, MAE, RMSE, MAPE, paired intervals) and clarifies timezone handling (America/Edmonton), which goes beyond the schema. This aligns with annotations; no contradiction.

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 with no wasted words. The core purpose is front-loaded, followed by return metrics and timezone. Every sentence earns its place, and the structure is clean.

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?

Given the presence of an output schema, the description need not detail return structures. It covers purpose, scope, unit, metrics, and timezone. Annotations handle safety, so an agent has everything needed to invoke correctly.

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 start and end are already well-documented including timezone interpretation. The description adds the inclusive/exclusive interval notation ([start, end)) and reiterates the timezone, which is slightly redundant but adds minor clarifying value. 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?

The description states a specific verb ('Compares'), a precise resource ('Alberta Internal Load forecast versus actual'), a defined scope ('[start, end)'), and unit ('MW'). It clearly distinguishes this from siblings like compare_market_periods, which compares market periods, not forecast vs actual.

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 implies use for forecast-versus-actual comparisons but does not explicitly state when to choose it over alternatives or mention any exclusions. Sibling tools like get_load or compare_market_periods exist, but no routing guidance is provided.

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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