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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description's job is to add beyond that — and it does: 15-second resolution, a one-hour window, and an explicit rate-limit/cost model (free within the daily allowance, then $0.001 USDC per call via x402). That pricing and cadence disclosure is real behavioral value not present in the structured fields.

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?

Two sentences, no filler: the data scope comes first and the cost condition second. Every clause carries information an agent needs before calling.

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?

With an output schema present, return values need not be explained, and with zero input parameters there is no schema gap to fill. The description covers what the resource is, its granularity, its window, and its cost — sufficient for an agent to decide and call 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 takes zero parameters, so the baseline is 4 per the rubric; there is nothing for the description to disambiguate. The window ('last hour') is a fixed scope rather than an argument, so no parameter semantics are needed.

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?

States a specific resource (grid frequency in Hz) with its sampling cadence and lookback window ('every 15 seconds, last hour'), which is enough to distinguish it from siblings like temperature, demand-*, or generation-now. It does not explicitly name a contrasting sibling, so it falls short of a 5.

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?

Usage is implied by the data scope (real-time frequency is only available for the last hour), and the pricing sentence tells the agent when calls become billable. There is no explicit when-to-use/when-not or named alternative among the many gb-electricity siblings, so this is minimum-viable rather than instructive.

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