eia_electricity_retail_sales

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

No annotations are provided, so the description carries full burden. It mentions data sources but doesn't disclose behavioral traits like rate limits, authentication requirements, data freshness/latency, error conditions, or response format. For a data retrieval tool with 7 parameters and no output schema, this leaves significant gaps in understanding how the tool behaves.

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 appropriately concise - two sentences that efficiently convey the data scope and sources. It's front-loaded with the core purpose. The only minor improvement would be explicitly stating this is a data retrieval/query tool rather than assuming 'Get' implies that.

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 7 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the returned data looks like (structure, format), doesn't mention pagination (though limit parameter exists), and provides no context about data availability, quality, or typical use cases. For a complex data query tool, more guidance is needed.

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 schema already documents all 7 parameters thoroughly with descriptions, enums, and examples. The description adds minimal value beyond what's in the schema - it mentions 'state and sector' and 'data columns' but doesn't provide additional context about parameter interactions or semantics. Baseline 3 is appropriate when schema does the heavy lifting.

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 clearly states the tool retrieves electricity retail sales data with specific components (sales by state/sector, customer counts, pricing) and cites EIA forms as sources. It distinguishes from siblings by focusing on retail sales rather than generation, capacity, or natural gas topics. However, it doesn't explicitly contrast with the most similar sibling (eia_electricity_state_profiles) which might also contain state-level data.

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 no guidance on when to use this tool versus alternatives. With 13 sibling tools including other electricity and natural gas datasets, there's no indication of when retail sales data is appropriate versus operational data, state profiles, or other datasets. The agent must infer usage from the title/description alone.

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