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

Annotations already declare readOnlyHint and idempotentHint, so the description's additional context is valuable rather than redundant. It discloses non-obvious behavior: time-bearing date strings are rejected, the market day can be 23/25 hours on DST-transition days, and returned units depend on the zone's trading currency. No contradiction with annotations.

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 compact and front-loaded: it opens with the benchmark label and formula, then adds date constraints, return semantics, and common values. Every sentence conveys necessary information with no filler or repetition.

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 read-only derived metric with an output schema, the description is complete enough to invoke correctly without reading the schema. It explains what is computed, the day model, date validation, returned fields, units, and common parameter values. The only minor omission, exhaustive zone codes, is addressable via the sibling list_zones tool.

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 0%, so the description must carry parameter meaning and largely does. It defines x via the formula and lists common values (1, 2, 4), explains date formatting and DST behavior, and ties zone to day-ahead clearing prices. It does not enumerate valid zone values, but the sibling list_zones covers that gap.

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 derived metric and defines it mathematically: 'TBx = sum(top X priced hours) − sum(bottom X priced hours) over the day-ahead clearing prices for zone on date.' It also names return fields and clarifies this is a battery-arbitrage benchmark, distinguishing it from raw price or flow siblings like get_day_ahead_prices and get_crossborder_flow.

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 intended use is made explicit through the 'daily battery-arbitrage benchmark' framing and the detailed definition of what the tool computes. It also gives practical constraints such as the bare YYYY-MM-DD date format and the SDAC market-day convention. It does not name sibling alternatives or state when not to use it, but the context is clear enough to guide selection.

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