How do I run the skill end-to-end?

Set RAIFFEISEN_ELBA_ID and RAIFFEISEN_ELBA_PIN as env vars, run login, then fetch accounts and transactions, and finally run logout to clear the session.

What output format is produced?

The tool outputs JSON containing balances, securities depot positions, and transactions suitable for automatic processing in downstream systems.

How should credentials be managed in CI or ephemeral runners?

Store credentials securely as environment variables or in a secret store, ensure login/logout flows run cleanly, and avoid exposing sensitive data in logs.

Raiffeisen ELBA

Verified

@odrobnik

npx machina-cli add skill @odrobnik/raiffeisen-elba --openclaw

Files (1)

SKILL.md

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Raiffeisen ELBA Banking Automation

Fetch current account balances, securities depot positions, and transactions for all account types in JSON format for automatic processing. Uses Playwright to automate Raiffeisen ELBA online banking.

Entry point: {baseDir}/scripts/elba.py

Setup

See SETUP.md for prerequisites and setup instructions.

Commands

python3 {baseDir}/scripts/elba.py login
python3 {baseDir}/scripts/elba.py logout
python3 {baseDir}/scripts/elba.py accounts
python3 {baseDir}/scripts/elba.py transactions --account <iban> --from YYYY-MM-DD --until YYYY-MM-DD

Recommended Flow

login → accounts → transactions → portfolio → logout

Always call logout after completing all operations to clear the stored browser session (cookies, local storage, Playwright profile). This minimizes persistent auth state on disk.

Source

git clone https://clawhub.ai/odrobnik/raiffeisen-elbaView on GitHub

Overview

Raiffeisen ELBA Banking Automation fetches current account balances, securities depot positions, and transactions for all account types in JSON for automatic processing. It uses Playwright to drive the ELBA web interface, enabling repeatable data exports for reconciliations and reporting. Entry point is {baseDir}/scripts/elba.py.

How This Skill Works

The skill exposes an entry point at {baseDir}/scripts/elba.py that uses Playwright to automate login, accounts, and transactions fetch. It requires environment variables RAIFFEISEN_ELBA_ID and RAIFFEISEN_ELBA_PIN for authentication. The output is structured JSON suitable for downstream processing and can include balances, positions, and transactions across accounts.

When to Use It

Automate end-to-end ELBA data extraction for reconciliation and reporting
Create periodic snapshots of balances, positions, and transactions for the portfolio
Generate JSON feeds for ERP or BI systems from ELBA data
Produce audit-ready exports for a specific date range
Automate daily/weekly ELBA data pulls with a clean login/logout cycle

Quick Start

Step 1: Set environment variables: export RAIFFEISEN_ELBA_ID=your_id; export RAIFFEISEN_ELBA_PIN=your_pin
Step 2: Start a session: python3 {baseDir}/scripts/elba.py login
Step 3: Retrieve data and end session: python3 {baseDir}/scripts/elba.py accounts && python3 {baseDir}/scripts/elba.py transactions --account <iban> --from YYYY-MM-DD --until YYYY-MM-DD && python3 {baseDir}/scripts/elba.py logout

Best Practices

Store credentials as environment variables (RAIFFEISEN_ELBA_ID, RAIFFEISEN_ELBA_PIN) and avoid hardcoding
Follow the recommended flow: login → accounts → transactions → portfolio → logout to minimize persistent sessions
Use explicit date ranges for transactions and validate JSON output against your schema
Handle timeouts and retries in Playwright; log errors and preserve stdout for debugging
Always run logout after operations to clear cookies and local storage

Example Use Cases

Monthly reconciliation: export all ELBA accounts and transactions for ERP integration
Portfolio reporting: fetch balances and securities depot positions for dashboards
Auditable export: generate a date-bounded JSON feed for compliance review
ERP integration: feed a JSON bundle into accounting software for automatic imports
Daily data pull: automated ELBA snapshot for a BI analytics pipeline

Frequently Asked Questions

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