Calcgrid

Add Mainland China Working Days

add_china_working_days

Read-onlyIdempotent

Use this when you need a deadline or settlement date a stated number of mainland China national working days before or after a 2024-2026 date. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery.

Do not use this when you need calendar days, a sector-specific settlement calendar, a local holiday calendar, or a result outside the 2024-2026 coverage. What it computes: Adds or subtracts official mainland China working days, skipping holiday periods and ordinary weekends while counting State Council-designated weekend makeup workdays. Example user requests: What date is 5 China working days after 2026-09-24, accounting for Mid-Autumn and National Day? | 从2026年9月18日起往后数5个中国工作日是哪天？ | Subtract 10 official mainland China business days from 2026-03-02. Inputs: start_date (date); working_days (integer, working days). Complete JSON argument examples: {"start_date":"2026-09-24","working_days":5} | {"start_date":"2026-09-18","working_days":5} Outputs: start_date, result_date, result_weekday, result_is_working_day, working_days_added [working days], calendar_days_elapsed [days], non_working_days_skipped [days], adjusted_workdays_counted, source_document_ids, dataset_version, coverage_start, coverage_end. Formula: move one calendar day at a time in sign(working_days); decrement the remaining count only when is_working_day(date) is true Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/china-add-working-days with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/everyday/china-add-working-days.md

Input Schema

TableJSON Schema

Name	Required	Description	Default
`start_date`	Yes	Starting mainland China civil date (YYYY-MM-DD), within 2024-2026.
`working_days`	Yes	Signed number of official working days to add; the start date is excluded when non-zero. Negative values move backward. Unit: working days.

Output Schema

TableJSON Schema

Name	Required	Description
`links`	No
`result`	Yes
`request`	Yes
`sources`	No
`success`	Yes
`version`	No
`freshness`	No
`timestamp`	Yes
`next_actions`	No
`service_version`	Yes	Deployed Calcgrid implementation version used for the result.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 27, 2026

addedOutput schema / properties / service_version

Added value: +{
+  "description": "Deployed Calcgrid implementation version used for the result.",
+  "type": "string"
+}

changedOutput schema / required

Previous value: -[
-  "success",
-  "request",
-  "result",
-  "timestamp"
-]New value: +[
+  "success",
+  "service_version",
+  "request",
+  "result",
+  "timestamp"
+]

Changed1 schema field changedSep 26, 2026

addedInput schema / examples

Added value: +[
+  {
+    "start_date": "2026-09-24",
+    "working_days": 5
+  },
+  {
+    "start_date": "2026-09-18",
+    "working_days": 5
+  }
+]

AddedSep 25, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds significant behavioral context beyond that: the step-by-step calendar-day iteration, the rule for decrementing only on working days, special handling of State Council-designated weekend makeup workdays, and the 2024-2026 coverage limit. No contradiction with annotations.

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?

The description is long but well-structured and front-loaded with the use case and exclusions before technical details. However, the Inputs and Outputs sections largely repeat what is already in the input schema and output schema, adding mild redundancy. Still, each major section serves a purpose.

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

Completeness5/5

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

Despite having an output schema and rich annotations, the description still supplies the algorithm, coverage bounds, and a direct REST fallback URL with a warning not to guess other paths. Everything an agent needs to invoke and return the result correctly is present.

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

Parameters3/5

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

Schema description coverage is 100%, and the schema already documents both parameters with format, units, minimum/maximum, and examples. The description only restates the inputs and complete JSON examples, adding little semantic 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.

Purpose5/5

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

The description uses a specific verb and resource: 'Adds or subtracts official mainland China working days,' and immediately distinguishes the tool with explicit exclusions (calendar days, sector-specific settlement calendars, outside 2024-2026). It also differentiates from sibling add_uk_working_days by making the 'China' scope explicit in both title and description.

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

Usage Guidelines5/5

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

The description gives explicit 'Use this when...' and 'Do not use this when...' conditions, including a clear exclusion for calendar days and out-of-range dates that map to potential alternatives. It also instructs the agent to call the tool directly and return its calculation rather than answering from memory, which is strong routing guidance.

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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