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Number to words (English & Arabic)

text_number_to_words
Read-onlyIdempotent

Convert numbers and currency amounts into English or Arabic words for cardinals, ordinals, cheque writing, and Arabic tafqeet, including decimals and currency sub-units.

Instructions

Spell a number in words in English and Arabic: English cardinal (with decimals, optional British "and"), ordinal (twenty-first), cheque wording for an amount in a currency (cents in words or as 25/100, optional "only"), Arabic cardinal, and Arabic tafqeet for amounts with correct gender/number agreement of the currency noun (optional "faqat … la ghayr" wrapper and the modern 100 spelling). Currencies: JOD, USD, SAR, AED, KWD, EGP, GBP (or none). Accepts Arabic-Indic digits and thousands separators. Up to 999 trillion (15 digits). Web version: https://s3eidat.github.io/number-words/

Input Schema

NameRequiredDescriptionDefault
onlyNoAdd "only" (English) and the Arabic "faqat … la ghayr" wrapper to amounts.
numberYesThe number or amount, e.g. "1500.250", "1,234,567.89", -12.05 (Arabic-Indic digits work too).
britishNoBritish English "and": one hundred and five.
currencyNoCurrency for cheque / tafqeet wording: none (default), JOD, USD, SAR, AED, KWD, EGP, GBP.none
subStyleNoCheque sub-units in words (twenty-five cents) or as a fraction (25/100).words
modernHundredNoArabic: use the modern spelling of "hundred" (without the extra alif).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, closed-world), so the description's added value is the operational envelope: 15-digit/999-trillion limit, acceptance of Arabic-Indic digits and thousands separators, and the supported currency set. It still doesn't clarify whether English and Arabic are returned together or selected by input, which is a behavior an agent needs.

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?

Front-loaded with the core action and tightly packed, with no filler sentences. However, the single long enumerative sentence is dense and mixes capability listing with usage hints, slightly reducing scannability.

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 no output schema, the description should pin down the return shape, and it mostly does by naming the phrasing styles produced. The remaining gap is whether a single call returns both English and Arabic renderings or one based on currency/style, which an agent must guess.

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%, so the baseline would be 3; the description goes further by tying each option to a mode — 'only' as the English only / Arabic 'faqat … la ghayr' wrapper, 'british' as the hundred-and form, subStyle as cents-in-words vs 25/100. This adds real interpretive value over the field descriptions.

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?

Opens with a specific verb+resource ('Spell a number in words') and immediately enumerates the distinct output modes (English cardinal, ordinal, cheque wording, Arabic cardinal, tafqeet). It is clearly distinguishable from neighbors like calc_roman or text_arabic.

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

Usage Guidelines4/5

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

Usage contexts are implied well through the mode list — cheque wording for currency amounts, tafqeet with gender agreement, British 'and' for UK spelling. It never names an alternative tool or states when NOT to use it, so it falls short of explicit 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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