ai-bug-triage
混合流水线能显著减少重复工单与人工分类成本，提高运维效率。
可能处理敏感 CI 日志或需访问仓库/CI 凭证
用确定性指纹结合 LLM 做缺陷分类、聚类去重并生成规范化工单与严重度判定。
把 CI 日志先做确定性指纹和聚类去重，再让 LLM 负责解释、判定严重度并生成规范化工单，把人从重复错误的枯燥分辨里解放出来。适合大量自动化测试或 CI 报错需要自动分类和写 ticket 的场景。优势在于把机器擅长的去重和 LLM 擅长的写作/判定分工清楚，既稳又高效。
▸ 展开 SKILL.md 英文原文
Hybrid fingerprint + LLM pipeline for bug classification, deduplication, and ticket generation. Normalizes CI logs, creates stable fingerprints, clusters near-duplicates, then uses LLM for severity classification and ticket writing. Includes bug reporting templates and severity/priority matrix. Use when: "bug triage," "classify bugs," "failure analysis," "auto-classify," "CI failures," "bug report," "defect template." Not for: runtime self-healing of one flaky locator — use test-reliability. Not for: designing new tests from production telemetry — use observability-driven-testing. Related: qa-metrics, qa-dashboard, ci-cd-integration, qa-project-context.
帮我安装这个 skill：https://raw.githubusercontent.com/petrkindlmann/qa-skills/main/skills/ai-bug-triage/SKILL.mdcurl -fsSL "https://raw.githubusercontent.com/petrkindlmann/qa-skills/main/skills/ai-bug-triage/SKILL.md"<objective> A hybrid pipeline for bug classification, deduplication, and ticket generation. Deterministic fingerprinting handles deduplication (what LLMs are bad at); LLM handles explanation, severity assessment, and ticket writing (what LLMs are good at). **Key reframe:** The LLM is best at explaining and routing, not deduplication. Teach agents to DESIGN the pipeline, not BE the pipeline. </objective> --- ## Discovery Questions Check `.agents/qa-project-context.md` first — it carries tech stack, component mapping, and known flaky areas that improve classification accuracy. Use it and skip anything already answered there. Then clarify: 1. **What is the failure source?** - CI pipelin