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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description goes further by explaining the data_confidence levels ('high' = officially announced, 'medium' = estimated) and the presence of estimated_items, sources and data_version. It also flags the half-day counting behavior. It stops short of describing weekend/weekday handling for private sector beyond what the schema says, so not a full 5.

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 operation and the output shape, with the example placed mid-text where it supports comprehension. The final sentence enumerating response metadata is slightly list-heavy but each element (confidence, sources, version) carries real decision value, so little is wasted.

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 an output schema present, the description needn't re-document return values, yet it usefully clarifies confidence semantics and half-day behavior. Combined with 100% schema coverage, an agent has everything needed to call this correctly; only edge behavior for private-sector weekend assumptions is left to the schema.

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 100% — the emirate, sector, inclusive and date parameters are all documented with defaults and semantics in the schema itself. The description's 'choose which endpoints to include' and the example reuse that information rather than adding syntax or format detail, 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 ('count working days between two dates') with explicit scope ('for a UAE emirate/sector') and what it returns (Friday half days, non-working day list). This is clearly separable from siblings like add_working_days or is_working_day, which operate on offsets or single dates.

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?

Names concrete use cases (leave calculations, payroll, project durations, lateness) and a worked example with parameters, which gives a strong sense of when to reach for it. However, it never explicitly excludes alternatives — e.g., it doesn't say to use is_working_day for a single date or add_working_days for offsets, so routing between siblings still requires inference.

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