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

Goes well beyond the readOnly/idempotent annotations by disclosing that private-sector weekends are employer-specific and only a flagged default is applied, plus the confidence model (high vs medium), estimated_items, sources and data_version. These are the exact caveats an agent needs before trusting the answer.

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-loads the core question, then usage, then an example, then response caveats – good ordering. It spends a sentence enumerating response fields (data_confidence, estimated_items, sources, data_version) that an output schema already covers, which is mild redundancy.

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?

For a 3-parameter lookup with full schema coverage and an output schema, everything an agent needs is present: scope, defaults, timezone handling for naive datetimes, and the reliability semantics of the answer. Nothing material is missing.

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 the schema already explains sector and emirate enums, so the baseline would be 3. The description adds real value with a worked example showing a full parameter combination and the resulting shape, plus the reminder that 'federal' is the safe default.

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?

Names a specific decision (does a datetime fall inside working hours for an emirate/sector) and enumerates the inputs that affect the answer (weekends, holidays, Friday half day, Ramadan hours). This clearly distinguishes it from date-level siblings like is_working_day and add_working_days.

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?

Provides explicit usage situations: 'Use before calling a government office, scheduling a meeting or promising same-day action.' It does not, however, explicitly route to or exclude the closest siblings (is_working_day, working_days_between), leaving that comparison to inference.

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