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

Annotations only cover read-only/open-world, so the description carries the behavioral load and does so richly: exact comparison windows, the drivers bridge structure, oneOffs handling of disposal/FX so a lumpy asset sale isn't read as a trend, integer-cents units, `direction` semantics relative to profit, and the periodic-stock COGS caveat that warns against misreading a missing COGS as margin gain.

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?

It is a long single paragraph but front-loads the core diagnostic purpose and then layers needed detail. Given there is no output schema, enumerating the return shape earns its place, though the prose is dense enough to be slightly heavy for a one-parameter tool.

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 fully enumerates the return shape (both net-profit windows, delta, drivers bridge, oneOffs, priorMonthFull, assumptions, notes), and covers edge cases and units, leaving nothing an agent needs in order to call and interpret it.

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% and there is only one optional param, so the schema already documents `month`'s format. The description adds genuine semantic value beyond it by clarifying that a completed past month compares its whole length while the default is current month-to-date against the same day-span.

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 ('diagnostic breakdown of WHY net profit moved') and explicitly frames it as deterministic decomposition rather than a generative model, which distinguishes it from siblings like income_statement or financial_timeseries that report rather than explain movement.

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?

Gives clear conditional guidance on the one parameter (omit `month` for current month-to-date; supply it to analyse a completed past month), and explains the comparison baseline. It does not, however, explicitly name an alternative sibling tool or say when to prefer this over income_statement, so it falls short of full routing guidance.

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