dedupe

Identify duplicate GitHub issues by semantically matching titles and bodies.

Updated Mar 19, 2026
One-click install
npx skills add https://github.com/japurcell/skills --skill dedupe
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dedupe
Source: https://github.com/japurcell/skills/tree/main/skills/dedupe
Command: npx skills add https://github.com/japurcell/skills --skill dedupe

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Find duplicate GitHub issues by semantically comparing a new issue against existing ones.

Core Features & Use Cases

  • Semantic duplicate detection across open and closed issues by comparing titles and bodies.
  • Supports multi-step analysis, term extraction, and similarity scoring to surface likely duplicates.
  • Use case: triage new issue by identifying existing discussions to avoid fragmentation.

Quick Start

Input a new issue reference and get back a list of potential duplicates.

Frequently Asked Questions about dedupe

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

FAQPage Schema
How do I find duplicate GitHub issues automatically?

Semantic duplicate detection compares a new issue against existing ones using titles and bodies. It works across both open and closed issues in a targeted GitHub repository, performing multi-step comparisons with configurable term extraction to surface likely duplicates for triage.

Can I detect duplicate issues across closed GitHub issues?

Yes, semantic comparison evaluates both open and closed GitHub issues. By analyzing titles and bodies across the entire repository history, it identifies existing discussions related to a new issue, helping maintainers avoid fragmentation and consolidate related topics.

What is the best way to triage new GitHub issues for existing discussions?

Using semantic similarity scoring is the best way to triage new GitHub issues for existing discussions. The Skill extracts configurable terms and evaluates similarity across issue titles and bodies to identify potential duplicates, consolidating related conversations effectively.

Does semantic issue matching require specific labels or metadata?

Semantic issue matching requires accessing issue data such as titles, bodies, and labels. The Skill utilizes this metadata to perform multi-step comparisons with configurable term extraction, evaluating similarity to accurately identify potential duplicates within targeted GitHub repositories.