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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description adds substantial context beyond them: the pinned 2027 dataset scope, the BKPP/JPM source, the computation formula, and a REST fallback URL with an explicit warning not to guess other /api/* paths. This is well above the annotation-covered bar.

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 usage and exclusions, then computation, examples, inputs, outputs, formula, fallback. Well-structured and scannable, but the enumerated Outputs list is redundant given an output schema exists, and the sectioning adds length beyond what is strictly needed.

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 2-param, no-nesting, closed-world, idempotent calculation tool with an output schema and full schema coverage, the description covers when to use, what is computed, dataset provenance, example invocations, and a fallback. Nothing an agent needs to invoke it correctly 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 description coverage is 100% and both parameters are fully documented (date format, division enum values), so the schema carries the load. The description's 'Inputs: date (date); division (enum)' essentially restates the schema, adding no new semantics, so the baseline 3 applies.

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+scope: a division-specific Malaysian public-holiday working-day check against BKPP/JPM's 2027 table. It is clearly distinguished from the dozens of sibling check_*_working_day tools (other countries) and from add_/count_ variants by naming the division-level federal/state granularity.

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?

Explicit when-to-use ('when you need a division-specific Malaysian public-holiday result'), explicit when-not-to-use ('division unknown', or employer/bank/exchange/school/inferred replacement-day calendars), plus a directive to call it directly rather than answer from memory. Nothing is left to inference.

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