How-to guide · Checked November 4, 2026

How to Audit Bank Rule Accuracy With ChatGPT

Preparation-only workflow using reviewed files and explicit outputs. Uploading Markdown is reference context, not a native skill installation or permission to act.

Audit fictional auto-categorized transactions against manual review.

1. Read the workflow and source

Open the complete free skill and authored Markdown download, its inputs and review gates. Read ChatGPT project documentation for current file, plan and privacy limits. Account access is not tested here.

2. Start with approved reference files

Create a separate conversation or project for this one job. Upload the public Markdown as reference if your account supports files. This is not a plugin installation. Do not mix clients or place credentials and private records into a reusable setup instruction.

3. Run the fictional acceptance test

Fictional month: 90 auto-categorized transactions; 81 match review and 9 are miscoded, 6 from one 'Office' rule. Expected result: flag 1 rule covering 9 transactions.

4. Use a narrow request

Use the attached Bank Rule Auto Categorization Accuracy Audit as reference. Audit only this fictional sample. Return rule, transactions, miscategorized and flag. Do not edit any rule.

5. Review before real data

Check each source row, unchanged original value, missing fact and arithmetic. A successful fictional result is a readiness check, not proof of real-account compatibility. Only then use authorized minimum-necessary real exports, confirm retention/access and ask the responsible owner to review the result.

Where this guide stops

No sending, sharing, ledger/CRM changes, account sign-in or spending is authorized by this guide. A separate request and the required approval govern real actions. Keep an evidence copy of the input version and reviewed output.

Checked November 4, 2026. Demand lead follows the published workflow topic; exact guide query volume is unmeasured. AI Agent Skills is independent of the named assistant maker.