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

With no annotations, the description carries the full transparency burden. It discloses the return format ('Returns a time series in EUR/MWh') and the time horizon ('day-ahead'), which is useful. However, it does not mention any potential side effects, validation behavior, or limitations (e.g., zone availability), leaving some gaps.

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 two sentences with zero fluff. It front-loads the core purpose, then adds usage context and return format. Every sentence earns its place.

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 simple one-parameter tool with no output schema, the description covers the essential aspects: purpose, usage scenarios, and return format. It could benefit from an explicit note on zone validation, but the schema already handles that, making the description sufficiently 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?

The schema has 100% coverage for the single 'zone' parameter, including guidance to use get_supported_zones if unsure. The description adds little beyond the schema, only restating 'for a zone.' The baseline of 3 is appropriate since the 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's core function with a specific verb and resource: 'Get tomorrow's (and near-future) hourly day-ahead electricity prices for a zone.' This distinguishes it from siblings like get_current_price (current prices), get_price_history (historical), and get_cheapest_window (a derived metric).

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 gives concrete use cases: 'typically used to show the full daily price curve, find low-price hours visually, or debug scheduling.' This provides clear context for when to use the tool, though it does not explicitly name alternatives or provide exclusions. The lack of explicit alternatives drops it from a 5, but the context is meaningful.

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