reference-data

settlement_date

PAID ($0.05). Settlement/value date: the date n business days after a trade date, computed on the INTERSECTION of the calendars you name, with a per-day trail showing every skipped day and why, on which calendar. Supply business_days for a cycle you are trading under, or market + instrument_class to have a settlement cycle applied that we cite to its primary source (e.g. US equities T+1 under 17 CFR 240.15c6-1(a); UK gilts T+1 by DMO convention, which is NOT the T+2 equity cycle; Japan equities T+2 but JGBs T+1). Calendars are NATIONAL statutory holiday calendars with researched statutory weekend rules (Israel Saturday-only, Gulf Friday+Saturday, India Sundays plus the 2nd and 4th Saturday), NOT CSD or exchange calendars — each response states the basis and any known divergence. Use 'eu.t2' for the euro cash leg. We refuse FREE rather than guess: beyond published calendar coverage, no cited cycle for the instrument (government bonds never inherit an equity cycle), a cycle not in force on the trade date, or FX spot value dates. Free companion: GET /settlement-conventions.

Input Schema

TableJSON Schema

Name	Required	Description
`market`	No	ISO country of the market whose cited cycle should apply (with instrument_class)
`api_key`	No	API key (bypasses x402; metered for invoicing)
`calendars`	Yes	Calendar ids to intersect: two-letter ISO country codes, plus 'eu.t2' for the euro cash leg
`trade_date`	Yes	Trade/reference date, YYYY-MM-DD. Day 0: never counted, never rolled.
`business_days`	No	The offset you are trading under (T+n)
`instrument_class`	No	Instrument class — a government bond never inherits an equity cycle

TDQS

A4.9/5.0

Behavior5/5

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

Discloses cost ($0.05), calendar type (national statutory, not CSD), refusal behavior, and output details (date with trail). With no annotations, carries full burden and performs excellently.

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?

Packed with useful information but slightly verbose. Front-loads purpose and cost, then details. Every sentence adds value, though could be slightly more concise without losing substance.

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?

Fully covers all aspects: computation method, edge cases, pricing, constraints, and output expectation (date + trail). No output schema, but description sufficiently explains what the tool returns.

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

Parameters5/5

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

Adds significant meaning beyond schema: explains business_days vs market+instrument_class interaction, calendar id format, trade_date base (day 0 never counted), and refusal conditions. Schema coverage 100% gives baseline 3, but description far exceeds.

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?

Clearly states it computes the settlement/value date using intersection of calendars with per-day trail. Distinguishes from sibling tools like count_working_days by specifying business-day offset and cycle citation.

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?

Explicitly describes when to use (specify business_days or market+instrument_class), provides examples of cycles, and states refusal conditions (no published coverage, no cited cycle, FX spot). Mentions free companion endpoint.

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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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct reference-data query: minimum wage check, income tax computation, VAT breakdown, working days, public holidays, series current/history/snapshot/catalog, and settlement date. There is no overlap; even get_series and get_series_history are explicitly separated as current vs. historical values.

Naming Consistency4/5

Most tools follow a clear verb_noun pattern (check_, compute_, count_, get_, list_). The one outlier is settlement_date, which is a noun phrase rather than verb_noun, but the deviation is minor and does not cause confusion.

Tool Count5/5

With 10 tools, the set is well-scoped for a reference-data server covering tax, labor, calendars, and settlement. Each tool serves a distinct purpose and none feel redundant or unnecessary.

Completeness4/5

The server provides strong coverage: discovery via list_series, current and historical series values, a bulk snapshot, and domain-specific computations for minimum wage, income tax, VAT, working days, holidays, and settlement dates. Minor gaps exist (e.g., no direct tool for social security contributions), but the core reference-data workflows are well supported.

Resources

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