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by com.tttkmbb
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UK Working Days Between Dates

count_uk_working_days
Read-onlyIdempotent

Use this when you need a 2024-2028 UK SLA, payroll, project or delivery-day count and the selected division's bank holidays must be excluded. 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 only elapsed calendar days, a local/employer/market calendar, another jurisdiction or dates outside 2024-2028. What it computes: Counts working and non-working dates in England and Wales, Scotland or Northern Ireland using the official GOV.UK bank-holiday list instead of a weekday-only approximation. Example user requests: How many England and Wales working days are there from 24 December 2026 through 4 January 2027? | Count Northern Ireland business days from 10 to 14 July 2026 inclusive. | How many Scottish working days fall between 1 and 20 June 2026? Inputs: start_date (date); end_date (date); include_start_date (boolean, optional); include_end_date (boolean, optional); division (enum, optional). Complete JSON argument examples: {"start_date":"2026-12-24","end_date":"2027-01-04","include_start_date":true,"include_end_date":true,"division":"england-and-wales"} | {"start_date":"2026-07-10","end_date":"2026-07-14","include_start_date":true,"include_end_date":true,"division":"northern-ireland"} Outputs: division, division_name, normalized_start_date, normalized_end_date, working_days [working days], non_working_days [days], calendar_days_counted [days], bank_holidays_counted, dataset_version, coverage_start, coverage_end, source_snapshot_sha256. Formula: for each included date: working_days += is_working_day(date); non_working_days += not is_working_day(date) Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/uk-working-days-between with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/everyday/uk-working-days-between.md

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
divisionNoGOV.UK bank-holiday division. England and Wales share one official list; Scotland and Northern Ireland have separate lists.england-and-wales
end_dateYesSecond range endpoint in YYYY-MM-DD format, within 2024-2028.
start_dateYesFirst range endpoint in YYYY-MM-DD format, within 2024-2028.
include_end_dateNoWhether the normalized later endpoint participates in the count.
include_start_dateNoWhether the normalized earlier endpoint participates in the count.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
linksNo
resultYes
requestYes
sourcesNo
successYes
versionNo
freshnessNo
timestampYes
next_actionsNo
service_versionYesDeployed Calcgrid implementation version used for the result.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • 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"
+]
  2. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, so the description adds value by revealing that it uses the official GOV.UK bank-holiday list instead of a weekday-only approximation, that it returns normalized dates and dataset metadata (dataset_version, source_snapshot_sha256), and that it should be used directly rather than deriving the formula. It also warns about the exact REST fallback path, preventing guesses.

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 organized into clear sections (use case, exclusions, what it computes, example requests, inputs, outputs, formula, REST fallback) and uses headings and bullets for scannability. The 2024-2028 scope, example requests, and complete JSON examples are useful, but the "Formula" line is somewhat redundant given the earlier prose, and the REST fallback and Docs URL could arguably be placed in a separate metadata section. However, overall the structure earns high marks.

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?

The description provides everything an agent needs: a precise operational scope, coverage range, input types and enums, complete JSON examples, a list of all output fields (including working_days, non_working_days, bank_holidays_counted, dataset_version, etc.), a direct REST fallback, and a docs URL. Given the output schema exists but is not shown, the explicit output list fully compensates, and the behavioral guidance leaves no ambiguity about when and how to invoke the tool.

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 coverage is 100% and each parameter already has a description, so the baseline is 3. The description adds practical value by listing all five inputs with type and optionality in one lineched to existing schema (e.g., "division (enum, optional)"), and by providing two complete JSON argument examples that show how to structure the call, including the optional boolean flags and division values. This goes beyond the schema's individual parameter descriptions by demonstrating full request composition.

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 opens with a specific verb ("count") and resource ("working days between dates") and states the exact domain (UK SLA, payroll, project or delivery-day count) along with the requirement to exclude division-specific bank holidays. It also calls out that it should be used instead of answering from memory, and lists concrete example user requests, making the purpose unmistakable and distinct from siblings like count_china_working_days or check_uk_working_day.

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 explicitly provides "Use this when..." and "Do not use this when..." conditions, naming exclusions such as elapsed calendar days, other jurisdictions, local/employer calendars, and out-of-range dates. It also instructs the agent to call the tool directly and return its calculation, which clearly rules out alternative behaviors like answering from memory or stopping at discovery.

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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