Power grid triangle: grid stress & energy inflation ($0.10)

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

No annotations are provided, so the description carries full burden. It discloses the cost ($0.10 USDC) and outlines the computed components (demand, renewables, inflation, cross-validation). However, it does not describe output format, data source recency, error handling, or whether the operation is read-only (likely but unstated). The lack of output schema compounds this gap.

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 description is compact (three sentences) and front-loaded with the main concept. It includes cost and examples without unnecessary details. Every sentence contributes value, though it could be slightly more structured (e.g., separate output description).

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?

Given the tool has no output schema and moderate complexity (computing a composite metric), the description omits important details: it does not specify the return format (JSON, fields, data types), how to handle invalid loc values, or whether results are cached or real-time. The target audience is mentioned, but usage context is incomplete for a tool with no structured output documentation.

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?

There is only one parameter (loc) with 100% schema coverage. The description adds context by giving example values (us-ercot, us-caiso, eu-germany) and stating it's a grid region id. Since schema coverage is high and description adds some examples, a score of 3 is appropriate.

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 explicitly states the tool's purpose: computing a 'Power grid triangle' combining demand pressure, renewable resources, energy inflation, and cross-validation for a grid region. It identifies the target audience (power/energy & macro/inflation traders, utilities) and provides example locations, clearly distinguishing it from sibling tools covering different domains like crop drought or flood risk.

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 indicates the tool is for traders and utilities interested in grid stress and energy inflation, and gives example loc values. However, it does not explicitly state when to use or avoid this tool relative to alternatives, nor does it specify prerequisites or typical use cases beyond the broad audience statement.

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