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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds meaningful behavioral context beyond them: it is a daily summary only and the raw 5-minute series is deliberately not exposed. This granularity limitation is not derivable from the annotations or schema and helps the agent avoid misusing the tool.

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 tight sentences, front-loaded with the core purpose before the granularity caveat and the sibling redirect. Every sentence earns its place with no redundancy.

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 read-only, 3-param tool, the description covers what is returned (daily min/max/mean), the unit, the scoping constraint, and the data-granularity limit. With annotations covering the safety profile and no output schema needed, nothing critical is missing.

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 coverage is 100% with all three parameters described (region enum, inclusive date range), so the schema does the heavy lifting. The description adds the $/MWh unit and 'one region' scoping but no syntax details beyond the schema, so baseline 3 is appropriate.

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?

States a specific verb and resource (daily min/max/mean RRP for one NEM region over a date range), including units ($/MWh) and the exact metrics returned. An agent can distinguish this from sibling tools like get_battery_revenue or get_rankings without opening the schema.

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?

Explicitly says to use it 'for price context around revenue or events' and routes the spike-detection case to list_events, which is a clear alternative. It gives when-to-use context and one concrete exclusion, though it doesn't cover other possible siblings (e.g., query_nem_data).

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