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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description still adds real behavioral context beyond that: the exact computation formula, the notion of 'authority-scope' calendar policies, and a documented REST fallback with a warning not to guess another /api/* path.

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 when/when-not guidance before computation details, which is the right order. It is somewhat long and includes mildly redundant example user requests, but every section (inputs, outputs, formula, fallback, docs) is structured and earns its place.

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 4-parameter read-only computation tool with an output schema, the description covers purpose, usage boundaries, inputs, an argument example, computation semantics, and a REST fallback. Nothing an agent needs in order to call 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 includes types, defaults, and examples, so the schema already documents all four parameters. The description largely restates them ('start_date (date); end_date (date); include_start_date (boolean, optional)') plus a complete JSON example, adding little meaning beyond the schema. 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, and scope: 'Counts authority-scope working and non-working dates in a range' for Germany. It is clearly distinguishable from siblings like check_de_working_day (single-day test) and add_de_working_days (additive), which the description's framing helps disambiguate.

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 says when to use it ('when you need an auditable Germany working-day count') and instructs the agent to 'Call this tool directly... instead of answering the formula from memory or stopping at discovery,' which is a notable anti-pattern warning. It also gives a when-not: schedules that are state/municipal/school/bank/TARGET/transport/collective-agreement/employer-specific are not inferred.

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