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Benjamin09e

wezas-africa-toolkit

Generer Paiement Mobile Money

generer_paiement_mobile_money

Generate Mobile Money payment deeplinks, USSD codes, and QR payloads for Wave, Orange Money, MTN MoMo, M-Pesa, and Airtel Money using operator, phone, amount, and country.

Instructions

Génère un lien profond, une syntaxe USSD et un QR payload Mobile Money (Wave, Orange Money, MTN MoMo, M-Pesa, Airtel Money). / Generate deeplinks, USSD codes and QR payloads for African Mobile Money payments.

Input Schema

NameRequiredDescriptionDefault
paysYes
montantYes
operateurYes
referenceNo
telephoneYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It clarifies that the tool generates payment artifacts rather than executing payments, and it lists supported operators. However, it does not state whether any payment is initiated, what validation or formatting rules apply, or what error conditions exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded, and contains no filler. The bilingual wording is appropriate for a bilingual tool and both sentences directly describe the generated artifacts and operator scope.

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

Completeness2/5

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

An output schema exists, so return values do not need detailed explanation. Still, for a five-parameter payment generator with no annotations and no schema descriptions, the description omits essential calling details such as phone format, amount currency, country handling, and reference semantics.

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

Parameters2/5

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

Schema description coverage is 0%, so the description should compensate for all five parameters. It provides useful operator examples (Wave, Orange Money, MTN MoMo, M-Pesa, Airtel Money), which partially helps operateur, but says nothing about telephone, montant, pays, or reference formats and constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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

The description uses a specific verb ('Génère') and names concrete resources: deeplinks, USSD codes, and QR payloads for African Mobile Money payments. It does not explicitly differentiate itself from related siblings such as lister_operateurs or valider_telephone, but the purpose is still clear.

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

Usage Guidelines2/5

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

The description states what the tool generates and lists supported operators, but gives no guidance on when to use it versus alternatives like lister_operateurs, valider_telephone, or info_pays. There are no exclusions, prerequisites, or usage conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.