cnb-cool-integration
针对 cnb.cool 的云原生构建（CNB Build）：生成/修改 .cnb.yml 流水线、触发规则、 构建环境、runner 资源、缓存、环境变量、手动触发与调试。 在接入、迁移、优化或排查 CNB 构建配置时使用。
Best use case
cnb-cool-integration is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
针对 cnb.cool 的云原生构建（CNB Build）：生成/修改 .cnb.yml 流水线、触发规则、 构建环境、runner 资源、缓存、环境变量、手动触发与调试。 在接入、迁移、优化或排查 CNB 构建配置时使用。
Teams using cnb-cool-integration should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cnb-cool-integration/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cnb-cool-integration Compares
| Feature / Agent | cnb-cool-integration | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
针对 cnb.cool 的云原生构建（CNB Build）：生成/修改 .cnb.yml 流水线、触发规则、 构建环境、runner 资源、缓存、环境变量、手动触发与调试。 在接入、迁移、优化或排查 CNB 构建配置时使用。
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# CNB 云原生构建（cnb.cool） ## 你要输出什么 - `.cnb.yml`（必选）：基于用户目标生成或最小改动修改，并解释触发与并发关系（pipeline 并发 / stage 串行 / job 并发）。 - 需要时额外输出： - `.cnb/web_trigger.yml`：需要“手动触发按钮/参数/选择目标构建”时。 - `.cnb/env/*.yml`：需要复用环境变量或跨仓库 `imports` 时（见 `references/env.md`）。 - 注意：若用户使用的是 CODING 平台的云原生构建（配置文件为 `.coding-ci.yml`），语法与变量机制（尤其 `exports/imports`、内置任务等）与本 CNB 有差异，应改用 `coding-ci` Skill。 ## 开始前先问（尽量一次问完） 1. 默认分支与触发分支：哪些分支要跑？是否需要 `$` 兜底配置？ 2. 事件：`push` / `pull_request` / `commit.add` / `web_trigger_*` / `schedule` / `api_trigger` 等需要哪些？ 3. 构建语言与命令：例如 Go/Node/Java，具体 `test/build/lint` 命令。 4. 构建环境：直接用 `docker.image`，还是 `docker.build`/`docker.devcontainer`？是否需要共享 `volumes`？ 5. 资源与速度：runner 需要多少 `cpus/mem/disk`？是否需要 `tags`？ 6. 缓存与参数：需要缓存什么（`node_modules` / `go` / `maven` / `npm cache`）？是否需要跨节点缓存（`docker:cache`）？是否需要 `exports` 传参？ 7. 发布与手动：是否需要 `docker build & push`、部署、以及 web_trigger 按钮？ ## 配置生成/修改流程 ### 1) 选用 `.cnb.yml` 结构 - **推荐**：`<branch> -> <event> -> [pipelines]`（最直观） - **需要跨分支复用**：使用 `imports` 或 YAML 锚点（见 `references/cnb-yml.md`、`references/file-reference.md`） ### 2) 写最小可跑的 pipeline - pipeline 内 `stages` 默认串行；stage 内 `jobs` 默认并发。 - 同一 `<branch>/<event>` 下多个 pipeline **并发**，并共享相同 docker 环境与 runner（见 `references/cnb-yml.md`）。 ### 3) 加入缓存与复用 - 用 `docker.volumes` 缓存目录（copy-on-write，跨 stage 复制；见 `references/cache.md`）。 - 需要跨节点共享时，用 `docker:cache`（见 `references/cache.md`）。 ### 4) 补齐触发与手动能力 - 分支匹配用 glob；不匹配时可用 `$` 兜底。 - web_trigger 的 event 为 `web_trigger_<button-id>`（需要 `.cnb/web_trigger.yml`；见 `references/web-trigger.md`）。 ### 5) 出问题先按这套排查 - 触发没跑：检查 branch glob、event 名、是否被 `skip-cnb`/`skip-cnb: <stage>` 跳过（见 `references/trigger-rule.md`、`references/recipes.md`）。 - 缓存没命中：确认 `volumes` 挂载路径一致；需要跨节点则改用 `docker:cache`（见 `references/cache.md`）。 - 需要进机排查：按 `login` debug 配置加一段可登录 stage（见 `references/debug.md`）。 ## 常见用户请求 → 你应加载的参考 - 只问“怎么写 `.cnb.yml`”：读 `references/cnb-yml.md` 与 `references/docker-and-runner.md` - 只问“触发规则/事件/分支匹配”：读 `references/trigger-rule.md` - 只问“env/imports/exports”：读 `references/env.md` - 只问“缓存/加速”：读 `references/cache.md` - 只问“手动触发按钮”：读 `references/web-trigger.md` - 只问“登录调试”：读 `references/debug.md` - 只问“Monorepo 按需构建 / Docker build&push / 跳过构建 / 超时 / 权限”：读 `references/recipes.md`
Related Skills
feishu-integration
Feishu (Lark) unified CLI for tasks, documents, wiki, bitable, messaging, approval, and Drive. Supports search/create/edit/publish/export across all modules. Use when reading/writing Feishu docs, searching docs or wiki, managing tasks, sending messages, creating approvals, exporting to Markdown, or any 飞书/Lark interaction.
coding-net-integration
Coding.net DevOps automation: MR lifecycle, CI operations (trigger/logs/stop), artifact registry, cross-project queries, remote file audit.
web-scraper
Web scraper with SPA/JavaScript rendering, page interaction, and JS execution. Two-tier engine (HTTP → Playwright browser). Smart discovery, batch fetch, interactive content extraction, OpenAPI parsing. Use when read_url_content fails, SPA rendering needed, or page interaction required.
pm-toolkit
自然语言 → Mermaid 图表（16 种）+ 网页原型，本地 Web 面板实时预览/导出。
mobile-testing
Android/iOS automated testing: device management, app install, performance profiling, log analysis, screenshot comparison, Maestro E2E orchestration.
llm-agent-dev
LLM Agent engineering: pattern selection (12-mode matrix), data simulation, convergence iteration. Covers intent routing, function calling, ReAct, MCP, prompt chaining, guardrails, evaluation.
image-studio
AI image generation and editing: e-commerce templates (hero/banner/detail/lifestyle), image refinement (background replace/remove, enhance, retouch, style transfer), icon extraction (bg-removal + detect + smart crop with transparent output).
es-analytics
Elasticsearch / SLS 只读数据分析：索引探索、mapping、聚合统计、日志搜索、时间序列、多 Profile。
doc-sentinel
Document-code change notification system: traceable doc-code binding via git tree hash, git-diff-driven reconciliation plans with confidence/risk metadata, and idempotent execution. Use when maintaining documentation freshness, detecting stale docs, or binding docs to source code.
agent-task-orchestration
Task decomposition and multi-agent orchestration with retry, checkpoint recovery, and real-time monitoring. Mixed Codex/Claude Code engine. Parallel/sequential execution.
agent-swe-team
Multi-agent SWE team built on the Workshop model. Full-stack vertical workers, meeting room with @mention notification, private pipes, shared task board. Git worktree isolation, Leader-driven coordination. Mixed Codex/Claude Code engine. Use when a task needs engineering depth beyond a single agent. NOT for simple task parallelism (use agent-task-orchestration) or design discussions (use agent-brainstorm).
agent-front-design
Frontend design blueprints with craftsmanship scoring, self-critique loops, and engineering handoff. Aesthetic intelligence against AI homogeneity. Use for: UI/UX design specs, design system creation, visual direction exploration, component design review, design-to-engineering handoff.