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

Annotations already declare readOnly, idempotent, and closed-world behavior, so the safety profile is covered. The description adds genuinely useful behavior beyond that — that results are paginated and that the page token is passed back — though it calls the token 'next_cursor' while the actual parameter is named 'cursor', a naming mismatch that could trip up an agent.

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, front-loaded sentences with zero filler: what it is, how pagination works, what comes back. Every clause carries information.

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 no output schema, the description does the right thing by enumerating returned fields and types, which is what an agent needs here. It stops short of explaining what 'series' actually contains (measures/categories) or result ordering, but the core contract is complete.

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 all five parameters (including the year vs year_gte/year_lte distinction and limit bounds) are documented in the schema. The description's 'Fields:' list describes return columns, not inputs, so it adds nothing to parameter semantics. Baseline 3 applies.

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 states a specific resource and scope ('Electricity production and use per year'), making it immediately clear what data comes back. It does not, however, differentiate itself from the sibling electricity_forecast, so an agent still has to guess which of the two fits a given question.

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?

There is no when-to-use guidance, no exclusion conditions, and no mention of the closely related electricity_forecast sibling. The agent gets a data topic but no routing signal.

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