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

Annotations already cover the read-only/idempotent safety profile, but the description adds genuinely useful behavior beyond them: daily-grain-only restriction, the fact that optimal's actual figure is MLF-adjusted and solved-days-only so totals won't match, and that energy_rev_mlf_adjusted is null (not zero) until the LP backcast runs. That null-vs-zero distinction is exactly the kind of trap an agent would otherwise misread.

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?

Front-loaded with the core purpose and grain, then routing guidance, then the MLF caveat. Dense but every sentence carries routing or semantics payload; the long parenthetical about get_battery_optimal is the only spot that could be trimmed.

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 carries the return-value burden and does so reasonably: names the revenue components (energy, FCAS), the daily grain, and the MLF-adjusted field with its null semantics. The full shape/naming of returned fields is not enumerated, but enough is given to call and interpret it correctly.

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%, so the baseline is 3; the description adds the daily-grain constraint that shapes how date_from/date_to can be used, plus returned-field nuance tied to the duid/lookup flow. It does not add syntax or format detail beyond the schema, so it sits just above baseline.

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+resource+scope: daily gross-spot revenue by market (energy + FCAS) for one battery DUID over a date range, with daily grain. It explicitly distinguishes itself from sibling get_battery_optimal, so an agent can route without opening either 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 claims the revenue-question territory ('This is the tool for total revenue questions') and gives a when-not clause for get_battery_optimal, including why its 'actual' figure is not a valid revenue source. This is the when/when-not/alternatives pattern at full strength.

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