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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds useful behavioral context beyond that: it depends on EIA API configuration, returns specific spot prices, is sourced from EIA, costs $0.02 USDC per call, and includes an example output. This meaningfully exceeds the structured annotation signal.

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 front-loaded with the triggering use case and return value, followed by a concrete example, source attribution, and cost. Every sentence earns its place and none are redundant. It is compact while covering purpose, output, cost, and caveat.

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?

For a zero-parameter read-only snapshot tool with no output schema, the description is complete: it states what data is returned, with units and a concrete example, names the data source, notes the API configuration dependency, and gives the per-call cost. An agent has enough to decide whether and how to call it correctly.

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?

The tool has zero parameters and schema description coverage is 100%, so the description cannot add parameter-level meaning. The description does explain what data the no-parameter call returns, which is the relevant semantic content here. Baseline 4 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 names a specific resource and data scope: 'Returns WTI crude and natural gas spot prices' from the EIA. It also grounds the purpose in concrete use cases (commodity brief, input cost analysis, CFO/investment brief), which clearly distinguishes it from the many sibling benchmark tools.

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 explicitly states when to use the tool: 'Use when current energy price data is needed for a commodity brief, input cost analysis, or energy sector context.' It doesn't explicitly name alternatives or exclusions, but the use-case framing is clear enough for an agent to select it appropriately.

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