get_prices

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

With no annotations, the description carries full burden. It discloses that prices exclude taxes, tariffs, and transport costs, and warns that tomorrow's prices may return 404 before 13:00 CET. This provides key behavioral context beyond the raw schema.

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 extremely concise: two sentences plus an important warning. Every sentence adds critical information without redundancy. The key purpose and notable behavioral note are front-loaded.

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 no output schema, the description explains the return format (array of 24 hourly entries with Copenhagen timestamps) and covers purpose, parameters, and key behavioral notes. It is complete for a simple fetch tool, though a brief comparison to siblings would strengthen context.

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 already describes both parameters with 100% coverage. The description adds value by explaining default behaviors (env var for area, 'today' default for date) and the 404 condition for date. This enhances understanding beyond the schema alone.

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 fetches hourly electricity spot prices for a given date and Danish price area, specifying the unit (DKK/kWh) and format (24 hourly entries). It distinguishes raw spot prices from consumer prices, aligning with sibling tools like get_cheapest_hours, which implies a complementary function.

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 implies when to use (to get raw spot prices) and notes that consumer prices are higher, but it does not explicitly tell when not to use this tool or mention alternatives like get_current_price or get_price_summary. Usage guidance is implicit rather than directive.

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