reconciliation

Matches bank statement transactions to ledger entries using configurable scoring.

Updated Jun 5, 2025
One-click install
npx skills add https://github.com/wangzitian0/finance_report --skill reconciliation
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reconciliation
Source: https://github.com/wangzitian0/finance_report/tree/main/.opencode/skills/domain/reconciliation
Command: npx skills add https://github.com/wangzitian0/finance_report --skill reconciliation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the complex process of matching bank statement transactions with internal accounting entries, reducing manual effort and improving accuracy.

Core Features & Use Cases

  • AI-powered matching: Utilizes a multi-dimensional scoring algorithm to suggest matches.
  • Confidence Scoring: Assigns a confidence score to each potential match.
  • Review Queue Management: Routes low-confidence matches for manual review.
  • Use Case: Automatically reconcile a month's worth of bank transactions, flagging only those with low confidence scores for a human accountant to verify.

Quick Start

Use the reconciliation skill to match statement transactions against ledger entries.

Frequently Asked Questions about reconciliation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate bank statement matching against internal ledger entries?

Bank statement matching is automated by using a configurable scoring algorithm to compare statement transactions against internal ledger entries, generating candidate matches and managing matched or unmatched states.

How does AI matching handle low confidence transactions during bank reconciliation?

AI matching handles low confidence transactions by assigning multi-dimensional scores based on amount, date, and description, routing matches below defined confidence thresholds into a review queue for manual verification.

Can I configure tolerance weights for date and amount when matching bank transactions?

Yes, transaction matching operates with defined weights for amount, date, description, business logic, and historical patterns, allowing you to configure specific tolerances and confidence thresholds for auto-acceptance.

What is the best way to match a month's worth of bank transactions with historical patterns?

The best way to match monthly bank transactions is using a multi-dimensional scoring algorithm that evaluates historical patterns alongside amount and date data, auto-accepting high confidence matches while flagging others for review.

How does confidence scoring separate auto-accepted matches from pending review transactions?

Confidence scoring separates auto-accepted matches from pending review by evaluating each candidate against specified confidence thresholds, routing high-scoring matches automatically and isolating low-scoring transactions for manual accountant review.