Automate triage and labeling of open GitHub issues by analyzing content.
npx skills add https://github.com/dyoshikawa/webseek --skill triage-issues-dyoshikawa
Please help me install this Agent Skill. Skill: triage-issues Source: https://github.com/dyoshikawa/webseek/tree/main/.rulesync/skills/triage-issues Command: npx skills add https://github.com/dyoshikawa/webseek --skill triage-issues-dyoshikawa
This Skill eliminates the manual overhead of managing incoming GitHub issues by automatically identifying unlabeled items and applying appropriate categorization based on their content.
Run the triage-issues skill to scan the repository for unlabeled issues and apply the correct labels based on their content.
High-intent search queries and answers about installing and using this skill.
Automate GitHub issue triage by scanning open unlabeled issues and applying labels like bug or enhancement based on analyzed content and metadata. This ensures no community feedback is overlooked during repository maintenance.
Yes, you need the GitHub CLI (gh) installed and authenticated to label issues automatically. The CLI handles the repository API interactions required to scan issues and apply categorization tags.
The best way to categorize a backlog of new GitHub issues is to run an automated triage skill that analyzes descriptions and comments to apply precise labels. This helps contributors find tasks marked as good first issue or help wanted.
Yes, you can automatically identify and label bug reports versus enhancements in GitHub. The triage mechanism analyzes issue content and metadata to distinguish between bugs, enhancements, and documentation needs before applying the correct tags.
Context-aware issue labeling works by analyzing the text of issue descriptions and comments to determine the appropriate category. It then applies precise labels automatically, ensuring consistent backlog management across the repository.
You should not use automated issue triage when your repository lacks a clear labeling taxonomy or when issues require complex human judgment that content analysis cannot provide. It is designed for consistent categorization of standard backlog items.
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