Classify a GitHub issue and generate a recommendation deck.
npx skills add https://github.com/houfu/lq-maintainer-agent --skill review-issue-houfu
Please help me install this Agent Skill. Skill: review-issue Source: https://github.com/houfu/lq-maintainer-agent/tree/main/skills/review-issue Command: npx skills add https://github.com/houfu/lq-maintainer-agent --skill review-issue-houfu
This skill solves the problem of attention routing and cognitive overload for maintainers by providing a structured, canon-aligned review of individual GitHub issues.
Invoke the review-issue skill by running the command /lq-maintainer:review-issue followed by the specific issue number you wish to analyze.
High-intent search queries and answers about installing and using this skill.
Automating GitHub issue triage involves performing a read-only review of individual issues to classify intent and generate a recommendation deck. This process evaluates contributions against project canon and ADRs to determine the appropriate resolution path.
Canon-aligned code review is a structured evaluation of GitHub issues that checks contributions against project-specific canon and architecture decision records. It categorizes issues into bugs, features, or questions to guide human decision-making.
Yes, reviewing issues locally requires integration with the GitHub CLI and local repository state. This ensures all findings and generated recommendation decks are grounded in the current project context.
To generate a recommendation deck, run the review command followed by the specific issue number. The engine evaluates the issue and outputs actionable recommendations like needs-info, decompose, proceed, design, or escalate.
Yes, the issue review process includes tone-gated communication to draft respectful, contributor-friendly responses. These drafts adhere to project conduct standards before any public interaction occurs.
Automated issue triage performs a read-only review and does not modify the issue directly. It requires local repository state access, limiting its use in isolated environments without full project canon context.
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