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

Annotations already declare this a safe, closed-world read, so the description's job is to add context, and it does: it discloses a confidentiality boundary that blocks per-person figures and explains the diagnostics covering people left out and unmeasurable inputs. It does not describe pagination, units, or result size, but for a single-period aggregate read the disclosure of the privacy limit is the substantive behavioral detail.

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 resource and its contents before the exclusionary note, and every clause carries content. It is slightly dense with dashes and parenthetical asides, but nothing is redundant or repeated from structured fields.

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 correctly takes on the burden of naming the returned measures, including the diagnostic counts, which is the right call for a one-parameter summary tool. Minor gaps remain around units or currency and how the fixed/variable split is expressed, but nothing prevents correct invocation.

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?

Only one parameter with 100% schema coverage, so the schema already explains the fiscal period id, its default, and the pointer to fin_periods. The description's phrase 'for a period in aggregate' is consistent with that parameter but adds no format or constraint information beyond it.

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 resource and scope — the aggregate wage fund for a fiscal period — and enumerates exactly what it returns: total accrued, headcount, fixed/variable split, and diagnostics. It also sharply delineates itself from per-person pay data, so an agent can tell what this tool will and will not give back.

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 rules out the most likely mistaken use — retrieving an individual's wages — and points to where that data actually lives (the cabinet, under that person's permission). What is missing is a positive trigger phrasing that contrasts it with aggregate siblings such as retail_payroll_summary, so the when-to-use side is inferred rather than stated.

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