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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds useful context — weekly cadence and metric meanings — but says nothing about pagination, row caps beyond the schema, or the shape/units of returned observations.

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?

Three short sentences, front-loaded with the dataset and cadence, then metrics, then filtering/defaults. No filler and nothing redundant.

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 no-required-parameter data query, the description plus 100%-covered schema gives an agent enough to invoke correctly. With no output schema present, a brief note on the returned time-series format/units would have closed the remaining gap.

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?

Schema description coverage is 100%, so the baseline is 3, but the description goes further by defining each metric value ('production' = US field production, 'refinery_inputs' = gross refinery inputs), which the enum descriptions alone do not. Region and default handling are also restated, adding modest extra meaning.

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 cadence: 'Weekly US crude oil supply data from EIA,' which cleanly separates it from siblings like eia_natural_gas, eia_gasoline_prices, and eia_electricity_state. The verb is implicit (a retrieval tool), so it stops short of the 'specific verb+resource' ideal, but an agent can identify the dataset unambiguously.

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?

It states the default behavior ('Default: national production') and that results can be filtered by PADD region, which implies usage. However, it never says when to choose this tool over adjacent ones such as eia_series_lookup or eia_energy_consumption, and offers no exclusions or prerequisites.

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