Heath Ledger is an AI-powered bookkeeping agent that automates transaction categorization and financial statement generation for Mercury and Stripe users.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install heath-ledger
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install heath-ledger using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Heath Ledger?
Heath Ledger is a sophisticated financial automation tool designed to bridge the gap between raw banking data and professional-grade financial reporting. By integrating directly with Mercury bank accounts and Stripe accounts, this skill pulls transaction data and uses a tiered categorization engine to organize expenses and revenue. It serves as a digital accountant that learns your business patterns, significantly reducing the manual effort required for monthly closes and tax preparation.
This skill is a prime example of the power of Openclaw Skills, offering a structured way to manage P&L statements, balance sheets, and cash flow reports through a combination of rule-based logic and advanced AI. Whether you are a solo founder or managing multiple entities, it provides a reliable, SQLite-backed ledger that improves its accuracy the more you use it.
Heath Ledger Use Cases
- Automating monthly or quarterly financial closes for startups using Mercury.
- Generating detailed P&L and Balance Sheet reports for tax preparation or investor updates.
- Categorizing thousands of bank transactions using a mix of deterministic rules and AI-driven logic.
- Reconciling Stripe gross revenue and fees against Mercury bank deposits for precise bookkeeping.
- Managing bookkeeping across multiple business entities with a shared learning system.
How Heath Ledger Works
- Initialize the local SQLite database to store transactions and categorization rules.
- Connect your Mercury bank account and optional Stripe account via API tokens to discover financial entities.
- Pull transaction data for a specific date range into the local database.
- Execute the categorization engine which applies entity-specific rules, global rules, and AI analysis to organize transactions.
- Review any low-confidence items and manually set categories to help the system learn.
- Generate a comprehensive 4-tab Excel workbook containing the P&L, Balance Sheet, Cash Flow, and transaction details.
Heath Ledger Setup
First, initialize the database and seed initial rules:
scripts/init_db.mjs
Connect your Mercury account:
scripts/connect_mercury.sh <MERCURY_API_TOKEN> [entity_name]
(Optional) Connect Stripe for better revenue accuracy:
scripts/connect_stripe.sh <entity_id> <stripe_api_key>
Then, pull transactions and categorize:
scripts/pull_transactions.sh <entity_id> <start_date> <end_date>
scripts/categorize.sh <entity_id>
Finally, generate the books:
scripts/generate_books.sh <entity_id> <start_date> <end_date> [output_path]
Heath Ledger Data Schema & Taxonomy
Heath Ledger utilizes a local SQLite database to maintain data integrity and persistence. This structured approach is a hallmark of high-quality Openclaw Skills.
| Component | Description |
|---|---|
| Transactions Table | Stores raw data from Mercury and Stripe including dates, amounts, and descriptions. |
| Categories Table | A hierarchical Chart of Accounts including P&L sections and cash flow classifications. |
| Rules Table | A tiered system of mappings (Entity-specific, Global, Seed) with confidence scores. |
| Entity Settings | Configuration for accounting basis (accrual/cash), fiscal year offsets, and fee rates. |
Heath Ledger Advanced Features
- Multi-entity support allows one instance to manage books for several different companies.
- Compounding learning system where manual corrections update the ruleset, increasing auto-categorization accuracy over time.
- Intelligent Stripe gross-up logic that calculates actual revenue even if only net deposits are visible in the bank.
- Advanced rule hierarchy that prioritizes human-confirmed mappings over AI-generated ones.
- Flexible accounting basis configuration to switch between cash and accrual reporting.
SKILL.md
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