Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Set up a complete CI/CD pipeline for a project. Detects the stack, then generates and validates GitHub Actions workflows, a Dockerfile, and a Makefile as one coherent pipeline. Use when asked to "set up CI", "add pipeline", "create GitHub Actions", "ci/cd setup", "automate builds", "containerize", or "add a Makefile".
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Announce at start: "I'm using the ci-pipeline skill to set up the pipeline."
Core principle: Generate, then validate, then fix. A pipeline that was never validated is not a pipeline — it is a guess that will fail on someone else's machine.
This skill is the orchestrator. It does not write workflows, Dockerfiles, or Makefiles itself — it detects the stack, calls the right generator, routes the output through the matching validator, and reports the result.
"set up CI", "add pipeline", "create GitHub Actions", "ci/cd setup", "automate builds", "add Docker", "containerize", "add Makefile".
Not for: debugging an existing pipeline that already runs (read it first), or infrastructure provisioning — see What NOT to do.
Before generating anything, detect. Guessing here produces a pipeline that builds the wrong thing correctly.
package.json, pyproject.toml, go.mod,
Cargo.toml, pom.xml, build.gradle, Gemfile.github/workflows/, .gitlab-ci.yml, Jenkinsfile,
.circleci/Dockerfile, docker-compose.yml, compose.yamlMakefile, package.json scripts, build.gradle,
Taskfile.ymlReport what you found before generating. If detection is ambiguous — two languages, a monorepo with per-package manifests — say so and ask which target the pipeline should build, rather than picking one.
Run in this order. Stop on a hard failure; do not generate the next artifact on top of a broken one.
Invoke github-actions-generator with the detected stack.
github-actions-validator — must pass before continuing..github/workflows/ci.yml, plus deploy.yml if a deployment
target is detected.Only if no Dockerfile exists, or the user asked for one. Invoke
docker-expert (section Dockerfile Generation).
docker-expert (section Dockerfile Validation) — must pass before continuing.Dockerfile, .dockerignore.Only if no Makefile exists. Invoke makefile-pro.
Makefile with the targets build, test, lint,
docker-build, clean.Run every applicable validator once more against the final, combined output and report the results. A generator that passed in isolation can still produce a set of files that disagree with each other — the combined pass is what proves the pipeline works, not the per-step passes.
This is the part that matters, and it is not optional:
If the validator cannot run in the current environment (no actionlint, no
Docker daemon), say that explicitly and report which checks were skipped. An
unavailable validator is not a passing validator.
Verify before calling this done:
.github/workflows/ci.yml exists and passes github-actions-validatorDockerfile exists (if applicable) and passes the docker-expert validatorMakefile exists and make test runs locally.github/workflows/ or an existing Dockerfile
without showing the diff first. Existing pipelines usually encode a reason
— a private registry, a matrix, a self-hosted runner — that a regenerated file
silently drops.helm-generator and the k8s skills exist for it.github-actions-templates for new work — it is superseded by
github-actions-generator.os-scripting (Bash script generation and ShellCheck validation) — helper scripts the
pipeline calls, when the workflow needs more than a Makefile targetgithub-actions-templates — superseded, kept for its existing patternsvercel-deployment — deployment specifics for Vercel targetsdeploy-incus — Forgejo-to-Incus push deployment아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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