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

Annotations already cover safety (readOnly/idempotent/non-destructive/openWorld=false), yet the description adds real behavioral context: no weekend substitution or bridge is inferred, work_schedule selects a planning calendar rather than a personal roster, and hours/pay/shifts/local schedules/future years are explicitly not computed. This is exactly the beyond-annotation disclosure the dimension rewards.

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?

Usage is front-loaded, which is good, but the description also enumerates a long outputs field list that duplicates the existing output schema and appends a formula and REST fallback that could be trimmed. Much of it earns its place, but several clauses are redundant.

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 read-only calculation tool with a full output schema and rich annotations, the description is complete enough: it defines scope, policy exclusions, and the enum's meaning. Since an output schema exists, the elaborate output enumeration is unnecessary rather than harmful.

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%, so the schema already documents all five parameters, and the baseline is 3. The description echoes the param list and clarifies that work_schedule selects a planning calendar, which is mildly additive but mostly restates structured data.

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+resource ('Counts working/rest dates in the explicitly selected Lithuania 2026 five-day or six-day planning workweek') and scopes it to a country and year, so it is easily distinguishable from the many sibling count_XX_working_days tools. The explicit example requests reinforce what is being computed.

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?

'Use this when you need an auditable Lithuania working-day count' plus 'Call this tool directly... instead of answering the formula from memory or stopping at discovery' gives clear usage context. The 'Do not use this when...' clause is grammatical nonsense and does not name a real alternative, so the exclusion guidance is weak, but the positive routing is solid.

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