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

Goes well beyond the readOnlyHint annotation: it documents a self-consistency invariant the agent can use to validate results, an edge-case rule for departures dated on the 31st, and a hard output cap of the 400 most recent buckets. These are exactly the traits that prevent misexpectation of results and are not derivable from annotations or schema.

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 value proposition, then the invariant, the edge case, and the cap — each sentence adds distinct information. Only 'Read-only.' is redundant with the readOnlyHint annotation.

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 usefully specifies the returned fields, the grouping unit, and the bucket limit, which is enough to predict the response shape. The remaining gap is the semantics of the date-range and organizational filter parameters, which matter when composing a query.

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 carries full burden, yet it only explains 'period' (allowed values and default). The five filter/date parameters (since, until, location_id, org_unit_id, position_id) get no meaning, format, or interaction guidance in either the schema or the description.

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 concrete verb-and-resource ('hiring and leaving over time') and enumerates the exact metrics produced — hired, left, net, headcount_end — plus the grouping dimension. An agent can tell this is a headcount time-series aggregation rather than a raw people list or a cohort analysis from the first clause alone.

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?

Usage is implied by the metric enumeration ('per period, how many were hired...'), but there is no explicit when-to-use or when-not-to-use statement, and no alternative tool is named for overlapping needs. The default-value hint ('default month') is the only operational guidance given.

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