分析 Azure DevOps 中 VS Code 滚动构建健康状况并定位失败提交范围
复制安装指令,让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "build-health" 技能: 1. 下载 https://raw.githubusercontent.com/microsoft/vscode-team-kit/main/build-health/skills/build-health/SKILL.md 2. 保存为 ~/.claude/skills/build-health/SKILL.md 3. 装好后重载技能,告诉我可以用了
请分析 Azure DevOps 中 VS Code 滚动构建最近 100 次运行情况,汇总成功率、失败次数、常见失败阶段,并输出一份构建健康报告。
一份包含成功率、失败趋势、主要故障阶段与简要结论的构建健康报告。
当前 VS Code 滚动构建为红色,请找出最近一次成功构建到当前失败构建之间的提交范围,并标记最可疑的破坏性提交。
返回导致失败的提交区间、可疑提交列表,以及每个提交的影响说明。
我正在负责 build champ 值班,请快速总结当前滚动构建状态,包括是否正在失败、失败持续了多久、最近是否有重复性故障,以及建议优先检查的方向。
一份适合值班响应的简明摘要,说明当前状态、故障持续时间、重复问题和排查建议。
Quickly diagnose the VS Code rolling build (Pipeline 111) on Azure DevOps. This skill has two modes:
The report file is the primary artifact. Generate it first, summarize what it shows, and only then ask whether the user wants heuristic culprit analysis.
main is red and you need to find where it brokeAlways produce a markdown report file before presenting conclusions.
/tmp/build-health/tmp/build-health/build-health-report.mdanalyze-builds.mjs --format markdown --report ...The report must contain these sections:
Current StatusBuild Table — sorted newest → oldestIncidents — sorted newest → oldest, with Incident #1 being the most recentTop Failure ReasonsSuggested Next StepUse the chat reply to summarize the report, not to replace it.
az) installed and authenticated (az login)dev.azure.com (the fetch script calls Azure DevOps REST APIs)The scripts live inside this skill directory at <skill-dir>/scripts/. Always invoke them by absolute path. Derive <skill-dir> from the absolute path of this SKILL.md.
Use these defaults unless the user asks for something else:
OUT_DIR=/tmp/build-health
REPORT_FILE="$OUT_DIR/build-health-report.md"
Run the fetch script from this skill directory. It downloads builds, timelines for failed builds, and log tails for failing test/compile tasks — all in parallel batches.
bash <skill-dir>/scripts/fetch-builds.sh --count 100 --out "$OUT_DIR"
Options:
--count N — Number of recent builds to fetch (default: 100)--out DIR — Output directory (default: ./build-data)--pipeline ID — Pipeline definition ID (default: 111)--branch NAME — Branch to filter (default: main)Run this in a terminal with mode=sync and a generous timeout (e.g. 300000ms). The script needs network access, so request unsandboxed execution if sandboxing is enabled.
Once the data is downloaded, always generate the markdown report file first:
node <skill-dir>/scripts/analyze-builds.mjs "$OUT_DIR" --format markdown --report "$REPORT_FILE"
This runs entirely offline against the downloaded data and produces a predictable artifact that the user can open and consume directly.
If you need a terminal-friendly version for yourself while working, optionally run:
node <skill-dir>/scripts/analyze-builds.mjs "$OUT_DIR" --format text
The markdown report includes:
…
用于创建和管理 AST 禁用规则,阻止特定代码语法或模式出现在编辑中。
从正确性、测试、安全与性能等维度进行深入代码审查并给出改进建议
为方案、设计与实现提供高质量第二意见,及早发现逻辑与缺陷问题
获取指定 GitHub 通知线程的详细信息,便于快速查看上下文与后续处理。
帮助 AI 代理读写记忆与规则,并按环境自动选择可用存储方案
为 GitHub 议题或拉取请求快速添加表情反应,提升协作反馈效率。
帮助开发者验证 Azure DevOps 流水线改动,快速排查构建与 YAML 配置问题。
分析代码库健康状况,识别死代码、循环依赖与架构漂移问题。
扫描项目依赖、密钥、许可证与代码健康,并给出可执行改进建议。
用于代码与分支审查,综合检查正确性、兼容性、架构、测试、性能与安全问题。
帮助用户定位并调用 MSBuild,灵活构建项目或解决方案并返回清晰报错。
基于代码差异生成规范化 Git 提交信息,并支持按逻辑分组提交