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

Beyond the provided annotations (readOnlyHint=true), the description conveys key behavioral guarantees, specifically that 'units and dates' are preserved, which is a vital technical detail for consumers of the output data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The definition is highly concise and front-loaded. It delivers the core function and crucial data limitations within two tight, efficient sentences without any fluff.

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

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

The definition is adequate for describing *what* is retrieved (regional averages). However, because parameter usage relies on external lookups ('The dataset catalog lists region and dataset keys'), the definition remains incomplete regarding the practical operational steps for parameter selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With a 0% schema description coverage, the definition defaults to a baseline score of 3. While the text clarifies the nature of the data being queried (regional averages vs. parcel-specific metrics), it adds no semantic meaning or guidance to the individual parameters themselves.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description immediately and clearly states the purpose: to retrieve state prices, energy, emissions, or hourly grid demand and fuel mix. This is highly specific.

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

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

The description provides crucial usage context by stating that the results are regional averages. It explicitly cautions the user that this data is not equivalent to parcel utility prices or available grid capacity, effectively defining its operational scope against potential alternatives.

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