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

Annotations already cover the read-only/idempotent/no-side-effect profile, but the description adds genuinely useful behavior the annotations do not: which closure categories are not inferred (collective-agreement, employer, sector, school, bank, local, customary half-day), the Store Bededag 2024 change, and the exact counting formula. It omits any range-limit or dataset-version caveat, but the added scope transparency is substantial.

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?

The labeled sections (when to use, when not, what it computes, inputs, outputs, formula, fallback, docs) are front-loaded and scannable. There is mild redundancy: the Inputs and Outputs enumerations largely duplicate the schema and output schema, and one example request is an awkward negation, but the structure remains easy to parse.

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?

An output schema exists, so return values need no explanation, and the description still covers scope, exclusions, formula, and a REST fallback path. What is missing is minor: no mention of the valid date window (2026-2027) or dataset currency, both of which live only in 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 coverage is 100%, so all four parameters are already documented in the schema. The description's 'Inputs' line and complete JSON example restate the schema rather than adding syntax, format, or default semantics beyond it, 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?

The description states a specific verb and resource ('Counts authority-scope working and non-working dates in a range') and pins the scope to Danish authority calendars. It distinguishes itself from the single-day check_dk_working_day by emphasizing range counting, but never names a sibling tool explicitly, so sibling disambiguation is inferred rather than stated.

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?

It gives an explicit positive trigger ('when you need an auditable Denmark working-day count'), an explicit exclusion ('Do not use this when nationwide statutory list only', plus the list of non-inferred closure types), and a directive to call the tool rather than answer from memory or stop at discovery. Nothing about when to invoke 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.