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datetime.add_business_days

Read-onlyIdempotent

Add or subtract business days from a start date while skipping weekends and country or extra holidays; return the resulting date in YYYY-MM-DD format.

Instructions

start_date 에 영업일 기준으로 days 를 더한(음수면 뺀) 날짜 end_date 를 YYYY-MM-DD 로 반환한다. 토·일, holidays 패키지의 country(기본 KR) 공휴일, extra_holidays 를 건너뛰고 시작일은 세지 않는다. days 는 절대값 100000 이하이며, 0 이면 시작일이 휴일이어도 그대로 반환한다.

Input Schema

NameRequiredDescriptionDefault
daysYes
countryNoKR
start_dateYes
extra_holidaysNo

Output Schema

NameRequiredDescriptionDefault
_metaNo서버가 붙이는 영수증(integrity), 엔진, 힌트
traceYes계산 근거(tool, formula, inputs, steps, output)
end_dateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.8/5.0
Behavior4/5

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

The annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, and the description still adds meaningful behavior: weekend and holiday skipping, KR default country, exclusion of the start date from the count, the absolute-value cap of 100000, and the special days=0 return. It does not discuss invalid country codes or error behavior, but its disclosure of behavior is well above the annotation baseline.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three dense sentences front-loaded with the return value and its format, then the skip rules, then the edge cases. Every sentence carries substantive information, though the enumeration of rules in the middle sentence is somewhat hard to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description need not explain return values, yet it still names the output field and format. All four parameters and the key edge cases are covered, so the description is close to complete; it does not state what happens when the inputs are invalid.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the full burden of explaining parameters; it does explain all four: start_date as the base date, days as a signed integer with a 100000 cap and defined 0-behavior, country as the holidays-package country code defaulting to KR, and extra_holidays as additional dates to skip. The remaining gap is that it never states the expected string format for start_date, extra_holidays, or country codes.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it adds signed business days to start_date and returns end_date in YYYY-MM-DD format. The business-day and holiday-skipping semantics make it clearly distinct from datetime.diff or datetime.count_business_days, but no sibling is named explicitly, so the definition does not achieve the highest level of differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives such as datetime.diff or datetime.count_business_days, and it names no exclusions. The usage is strongly implied by the precise semantics, which is the minimum viable level.

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

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