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Setup Favepay

Community
afu-it
setup-favepay

Set up, build, debug, review, and explain FavePay (Fave / FaveBiz) payment integrations using official Fave docs, the FavePay Omni (FPO) API, hosted web_url checkout, dynamic and static QR, merchant scan, webhooks, HMAC-SHA256 sign generation and verification, AES-128-CBC encrypted omni_ref redirects, transaction lookup, acknowledge, cancel QR, list transactions, full and partial refunds, sandbox UAT with test=true, and the official FavePay for WooCommerce plugin. Use when working with FavePay Malaysia or Singapore, Fave app QR payments, cards, DuitNow, GrabPay, ShopeePay, Alipay, WeChat Pay, Atome, Cashback, eCards, omni_reference, app_id, outlet_id, webhook settlement, refunds, or production readiness.

Overview

Publisherafu-it
Repositorymalaysia-payment-gateway
Skill namesetup-favepay
Stars
74
Forks
11
Bundled files
4
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by afu-it on GitHub. Read the source before you install it.

Installation

Install the Setup Favepay AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/afu-it/malaysia-payment-gateway/tree/main/setup-favepay
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/afu-it/malaysia-payment-gateway.git /tmp/malaysia-payment-gateway
mkdir -p .claude/skills
cp -r /tmp/malaysia-payment-gateway/setup-favepay .claude/skills/setup-favepay
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Setup Favepay in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Setup Favepay on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Setup Favepay is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

FavePay (FavePay Omni) Payment Gateway

Use this skill for FavePay Omni (FPO) integration work.

Source

Read references/favepay-api.md before giving factual API guidance or writing integration code. It holds environments, the signing algorithm with a verified worked example, the endpoint catalogue, full field tables for create, merchant scan, static QR, webhook, lookup, acknowledge, cancel, list and refund, statuses, errors and plugin behaviour.

Read references/account-setup.md when the user asks how to register, which credentials Fave issues, sandbox UAT and sign-off, env var names, payment methods, plugins, pricing or settlement.

Read references/source-map.md when choosing which official page or plugin file supports a fact.

Core Workflow

  1. Identify environment: Sandbox (https://omni.dino.fave.ninja) or Production (https://omni.myfave.com). Credentials are separate per environment.
  2. Identify country path segment: my (MYR) or sg (SGD). Currency follows the path; there is no currency field.
  3. Identify flow: online checkout (format=web_url), in-store dynamic QR (txt, base64, favepay), wallet QR (grab, alipay, wcp, shopeepay, atome, paynow), merchant scan, or static QR (planned).
  4. Create a local pending payment with a unique omni_reference (<Fave prefix>-<id>, max 28 chars) before calling Fave.
  5. POST /api/fpo/v1/<cc>/qr_codes server-side with total_amount_cents, app_id, outlet_id, format, redirect_url, callback_url, and sign last.
  6. Redirect the customer to code (for web_url), or render the QR payload or image.
  7. Treat the redirect back to redirect_url as browser UX only.
  8. On the webhook, verify sign over the received fields in received order, then return HTTP 2XX quickly and process idempotently.
  9. Confirm with GET /api/fpo/v1/<cc>/transactions (by omni_reference or receipt_id) when the webhook is late or missing.
  10. Cancel unpaid QRs with POST .../transactions/cancel; refund paid ones with POST .../transactions and status=refunded (same calendar day by default).

Core Facts

  • Production base: https://omni.myfave.com. Sandbox base: https://omni.dino.fave.ninja. All paths start /api/fpo/v1/<country_code>/.
  • Auth is a sign field: lowercase hex HMAC-SHA256 of the URL-encoded fields (form encoding, space as +) in the order sent, keyed with the Fave secret key.
  • Always exclude sign and country_code from the signing string; also exclude path outlet_id (list), path id (acknowledge) and details (merchant scan).
  • Do not sort keys. Nested objects flatten to bracket form, for example shopper_details[email]=....
  • Amounts are integer cents (total_amount_cents). Most response amounts are strings.
  • Create response: code, format, expires_in (seconds). Default format is base64.
  • Webhook statuses: successful and rejected. Expired or cancelled unpaid QRs can send rejected.
  • status_code: 0 pending_payment, 1 payment_processing, 2 successful, 3 disputed, 4 rejected, 5 refunded.
  • Transaction id prefixes: FP_ FavePay, RPP_ DuitNow, GRAB_, PAYNOW_, EXT_ other wallets.
  • Fave retries non-2XX webhooks at increasing intervals; the same payment can arrive more than once.
  • test=true on create (sandbox only) returns a test page URL in code to simulate success or failure. Never send it to production.
  • Errors use error and error_description. Bad sign is 401; unknown app_id is 404 resource_not_found; duplicate omni_reference is 400 validation.
  • Refund window: same calendar day by default (stale_transaction after). Partial refunds not supported for DuitNow or PayNow.
  • Rate limits and webhook source IPs: not documented in official docs (checked 2026-10-21).

Critical Rules

  • Keep the secret key and app_id server-side; the key signs requests, verifies webhooks and decrypts omni_ref.
  • Build the signing string from the exact fields you send, in the exact order you serialise them; put sign last.
  • Encode like PHP urlencode / http_build_query: space to +, everything except A-Z a-z 0-9 - _ . percent-encoded (uppercase hex).
  • Verify webhooks over the received JSON keys in received order (use an order-preserving parser), and compare with a constant-time check.
  • Do not mark paid from the redirect alone. Mark paid only after a verified webhook or a signed GET /transactions returns successful.
  • Check omni_reference, total_amount_cents, currency, outlet_id and status against the local record before settling.
  • Settle idempotently keyed on receipt_id or id; duplicate webhooks are expected.
  • Generate a new omni_reference for every new QR on the same order; references must be unique.
  • Use sandbox keys only with the sandbox base URL; Fave issues new production keys after UAT sign-off.
  • Confirm static QR availability with Fave before use; the docs mark it as planned.

Completion Criteria

A FavePay integration is done only when:

  1. QR or web_url creation runs server-side with a correct sign, and returns code.
  2. The redirect page shows status only, or re-queries the transaction server-side before showing success.
  3. The webhook URL is registered with Fave (kick-off meeting) or passed as callback_url, per environment.
  4. The webhook handler verifies sign, returns 2XX fast, and settles once per payment.
  5. Settlement checks reference, amount, currency, outlet and successful status.
  6. A scheduled requery handles missed webhooks; static QR flows call Acknowledge.
  7. Tests cover bad sign, duplicate webhook, wrong amount, rejected, expired QR, cancel, full refund, and stale_transaction.
  8. The UAT checklist (A1 to A4, B1 to B2, C1, D1 to D3) is passed in sandbox before asking for production keys.

Loophole Review Loop

When asked whether a FavePay strategy is "100% confident", run this loop until no factual gaps remain:

  1. List trust boundaries: browser redirect, omni_ref decryption, backend QR creator, Fave Omni API, webhook receiver, JSON parser key order, database, fulfilment job, refund job, POS display, and FaveBiz dashboard.
  2. Check bypasses: forged redirect, forged webhook, sign computed over sorted or re-serialised fields, wrong encoding (%20 vs +, ~, *), null or boolean values, sandbox key in production, test=true in production, reused omni_reference, wrong outlet, amount mismatch, duplicate webhook, late success after cancel, refund after the same-day window.
  3. Add fixes: server-side create, local pending record first, order-preserving verification, constant-time compare, strict amount and reference checks, idempotent settlement, requery fallback, per-environment config, cancel before reissuing a QR.
  4. Re-read references/favepay-api.md sections relevant to any gap.
  5. State remaining uncertainty where docs are silent: omni_ref IV and padding, boolean and null encoding in sign, rate limits, webhook IPs, retry schedule, settlement timing, pricing.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Setup Favepay AI skill do?

Set up, build, debug, review, and explain FavePay (Fave / FaveBiz) payment integrations using official Fave docs, the FavePay Omni (FPO) API, hosted web_url checkout, dynamic and static QR, merchant scan, webhooks, HMAC-SHA256 sign generation and verification, AES-128-CBC encrypted omni_ref redirects, transaction lookup, acknowledge, cancel QR, list transactions, full and partial refunds, sandbox UAT with test=true, and the official FavePay for WooCommerce plugin. Use when working with FavePay Malaysia or Singapore, Fave app QR payments, cards, DuitNow, GrabPay, ShopeePay, Alipay, WeChat Pa...

Why use Setup Favepay on TypingMind?

Because you install it once and use it with any model. Setup Favepay is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Setup Favepay in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/afu-it/malaysia-payment-gateway/tree/main/setup-favepay. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Setup Favepay?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Setup Favepay?

As many as you like. As long as a model supports skills, you can use Setup Favepay with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Setup Favepay AI skill free?

It is published on GitHub by afu-it. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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