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banking-intelligence

by ai.ohmyfin

bank_holidays

Get bank/public holidays for a country with payment impact analysis.

Returns all public holidays plus a 'payment_impact' section that shows:

  • Whether today is a business day or holiday in this country

  • Upcoming holidays in the next 14 days

  • Recent holidays in the last 14 days — for diagnosing a payment that is ALREADY stuck ("in progress for N days", "sent X days ago"). A recent holiday only counts if BOTH hold: it falls INSIDE the payment's own window (on or after the send date), AND its 'costs_a_business_day' is true. One that predates the send date is irrelevant, and one on the country's banking weekend closed nothing that was open — neither may be subtracted or given to the user as a cause. An empty list affirmatively means no recent holiday explains the delay — do not invent one from training data.

  • Every holiday entry (upcoming, recent, and next_holiday_after_today) carries 'costs_a_business_day'. Roughly one holiday date in six lands on its own country's weekend and shortens nothing; check the flag before quoting a holiday as a delay, a closure or a reason a window was short.

  • elapsed_business_days_by_send_date — the AUTHORITATIVE elapsed business-day count keyed by send date (weekends + this country's holidays already excluded). Use it verbatim instead of hand-counting.

  • Next business day and how many consecutive non-business days remain This context helps determine if holidays are causing payment delays.

Args: country_code: ISO 3166-1 alpha-2 code (e.g., "US", "DE", "GB") year: Year (default: current year). Range: 2020-2030.

Examples: bank_holidays("US") bank_holidays("DE", 2026) bank_holidays("GB", 2025)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
country_codeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries full burden and excels. It reveals the internal logic of payment_impact analysis, the meaning of 'costs_a_business_day', the conditions for a holiday to count, and the authoritative nature of elapsed_business_days_by_send_date. It also warns against misinterpreting empty lists, providing transparent boundaries.

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 organized with sections and bullet points. Every paragraph adds value; however, the diagnostic bullet is dense and could be tightened. It is not as concise as a two-sentence description, but length is justified by complexity.

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 covers purpose, parameters, return sections, edge cases, and examples. It anticipates the user's diagnostic needs and explains the semantics of the output. For a tool with two parameters and no annotations, it is exceptionally complete.

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?

Schema description coverage is 0%, so the description fully compensates. It defines country_code as ISO 3166-1 alpha-2 with examples, and year as optional with default current year and a range 2020-2030. Both parameters are clearly explained and mapped to usage.

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+resource: 'Get bank/public holidays for a country with payment impact analysis.' It clearly distinguishes this tool from siblings like is_business_day_check and country_banking_rules by focusing on the payment impact analysis, not just listing holidays.

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 states when to use: 'for diagnosing a payment that is ALREADY stuck' and provides decision rules for interpreting recent holidays. It includes a caveat to not invent holidays from training data, and directs to use the authoritative business-day count 'verbatim instead of hand-counting.' This goes beyond vague context to actionable guidelines.

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

A4.3/5.0
Disambiguation4/5

Most tools have distinct purposes, but some overlapping areas (goods_classify vs hs_code_lookup vs eccn_lookup; fx_rate vs fx_rate_history vs fx_volatility) require close reading of descriptions to select correctly. The detailed descriptions help, but the shear number of lookup tools creates mild ambiguity.

Naming Consistency3/5

Names mix verb-first (track_payment, mcp_verify) and noun-first patterns (iban_validate, fx_rate, ssi_lookup), with some phrase-like names (banks_using_correspondent, is_business_day_check). While readable, there is no single consistent convention.

Tool Count3/5

33 tools is heavy, but the server's broad scope (payments, FX, sanctions, export controls, company registries, SWIFT) justifies most of them. A few marginal tools (mcp_register, mcp_verify, company_search_result) add bulk without core value.

Completeness5/5

The tool set covers the payment lifecycle end-to-end: tracking, settlement, FX, compliance, sanctions, and company due diligence. There are no obvious dead ends; the tools chain together via next_steps and search_id flows.

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