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Issue Analysis with Label Inference

Infer labels from Miyabi's 57-label system for GitHub Issues.

Updated Jan 10, 2026
Search Tags:#automation#workflow#github#triage#ai-assistant#issue-labeling#label-inference
One-click install
npx skills add https://github.com/hiromima/collaborative-canvas --skill issue-analysis-with-label-inference-hiromima
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Issue Analysis with Label Inference
Source: https://github.com/hiromima/collaborative-canvas/tree/main/.claude/skills/issue-analysis
Command: npx skills add https://github.com/hiromima/collaborative-canvas --skill issue-analysis-with-label-inference-hiromima

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the laborious task of analyzing GitHub Issues and inferring consistent labels from Miyabi's 57-label system, reducing manual triage time and improving labeling consistency.

Core Features & Use Cases

  • Analyze issue title, body, and comments to infer appropriate labels across all 11 categories.
  • Support label inference for creation-time labeling and ongoing triage.
  • Provide a structured payload with recommended labels and rationale for downstream automation.

Quick Start

Input the issue details and receive inferred Miyabi labels with rationale for automation.

Frequently Asked Questions about Issue Analysis with Label Inference

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

FAQPage Schema
How do I automate GitHub issue triage with AI label inference?▼

Automate GitHub issue triage by analyzing issue titles, bodies, and comments to infer appropriate labels from Miyabi's 57-label system. This Skill returns a structured payload of recommended labels with rationale, suitable for integration into automation pipelines.

What is Miyabi's 57-label system for GitHub issue labeling?▼

Miyabi's 57-label system is a structured categorization framework spanning 11 categories used for GitHub issue triage. This Skill identifies and infers appropriate labels from this system to improve labeling consistency and reduce manual triage time.

Can I use this AI assistant for issue creation-time labeling and backlog prioritization?▼

Yes, you can use this AI assistant for both issue creation-time labeling and ongoing backlog prioritization. It analyzes issue details to infer labels and provides a structured output with rationale suitable for automation workflows.

How do I get structured label suggestions with rationale for automation pipelines?▼

Get structured label suggestions by inputting issue details into the Skill, which analyzes the content and returns a structured set of inferred Miyabi labels with justification. This output is designed specifically for downstream automation pipelines.

Does the label inference process analyze issue comments or just the issue body?▼

The label inference process analyzes issue comments as well as the issue title and body. By evaluating all available issue details, it identifies the most appropriate labels across all 11 categories of Miyabi's system.

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