ibank-worklog-duplicate-audit

Audit iBank worklogs for duplicate pairs and generate minimal revision JSON.

Updated Jun 5, 2026
One-click install
npx skills add https://github.com/KangJiSseok/ACODIAN --skill ibank-worklog-duplicate-audit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ibank-worklog-duplicate-audit
Source: https://github.com/KangJiSseok/ACODIAN/tree/main/.codex/skills/ibank-worklog-duplicate-audit
Command: npx skills add https://github.com/KangJiSseok/ACODIAN --skill ibank-worklog-duplicate-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audit iBank worklogs for exact duplicates, same-task duplicates, or same-title suspicious pairs, then prepare team-lead judgments and minimal clarification rewrites. Use when the user suspects duplicated worklogs or wants merge, delete, or clarify candidates.

Core Features & Use Cases

  • Identify exact duplicate rows
  • Detect same-task and same-title suspicious pairs
  • Route suspects to team lead and record judgments
  • Generate minimal revision JSON for revise pairs
  • Produce a new version like v6

Quick Start

Run the audit workflow on iBank worklogs to identify exact duplicates, same-task candidates, and same-title pairs, then generate lead-reviewed clarifications and minimal revisions.

Frequently Asked Questions about ibank-worklog-duplicate-audit

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

FAQPage Schema
How do I audit iBank worklogs for exact duplicates and same-task pairs?▼

To audit iBank worklogs for duplicates, you apply a detection workflow that identifies exact duplicate rows, same-task pairs, and same-title anomalies. It then produces per-pair judgments for merge, delete, or clarify actions.

What is the best way to generate minimal revision JSON for duplicate worklog entries?▼

Generating minimal revision JSON for duplicate worklog entries involves routing suspected pairs to a team lead for review, then automatically producing concise JSON rewrite suggestions for entries that require clarification.

How does same-title anomaly detection work for cross-team worklog datasets?▼

Same-title anomaly detection for cross-team worklog datasets works by applying pairwise analysis across cross-title scenarios. It flags suspicious pairs sharing identical titles to assemble candidate actions for team lead review.

Can I use this audit workflow for cross-title scenarios in an iBank environment?▼

Yes, you can use this audit workflow for cross-title scenarios in an iBank environment. It processes worklog datasets typical for iBank, covering cross-team scenarios and generating per-pair judgments for anomalies.