Ci pipeline

Skill viknesh20-20/claude-code-tool-kit/.claude/skills/ci-pipeline

Production-ready Claude Code configuration. 12 original agents, 200+ slash-command skills, 45+ MCP servers, 14 plugins, design + 3D + WebGPU + GSAP + RAG tooling. One-command Node.js installer for premium websites, SaaS apps, AI agents. Free, MIT, stack-agnostic.

Install

npx -y skills add viknesh20-20/claude-code-tool-kit --skill ci-pipeline

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One thing to look at

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What its author says it does

Copied from the file, not written here

Generates a CI/CD pipeline configuration for the project. Auto-detects the stack and creates GitHub Actions, GitLab CI, or other CI configs with lint, test, build, and deploy stages.

SKILL.md

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CI Pipeline Generator

Detect Project Stack

!ls package.json requirements.txt pyproject.toml go.mod Cargo.toml *.csproj *.sln Gemfile composer.json mix.exs Makefile Dockerfile 2>/dev/null !ls .github/workflows/ .gitlab-ci.yml Jenkinsfile .circleci/ .travis.yml bitbucket-pipelines.yml 2>/dev/null !cat package.json 2>/dev/null | grep -E '"(scripts|devDependencies)"' -A 10 | head -20

Pipeline Design

Step 1: Detect Requirements

From project files, determine:

Language and version (Node 20, Python 3.12, Go 1.22, etc.)
Package manager (npm, pnpm, yarn, pip, poetry, cargo, etc.)
Test command
Lint command
Build command
Required services (database, Redis, etc.)

Step 2: Generate Pipeline Stages

Stage 1: Install

Cache dependencies for fast subsequent runs
Use lock file hash as cache key

Stage 2: Lint

Run linter (ESLint, ruff, golangci-lint, clippy, etc.)
Run type checker if applicable (tsc, mypy, go vet)
Run formatter check (prettier, black, gofmt)

Stage 3: Test

Run unit tests with coverage
Run integration tests (with service containers if needed)
Upload coverage report

Stage 4: Build

Production build
Verify build artifacts are created

Stage 5: Security (optional)

Dependency vulnerability scan
Secret scanning
SAST if available

Stage 6: Deploy (placeholder)

Staging deployment (on push to main)
Production deployment (on tag/release)
Mark as manual/approval required

Step 3: Platform-Specific Output

GitHub Actions:

name: CI
on: [push, pull_request]
jobs:
  ci:
    runs-on: ubuntu-latest
    steps: ...

GitLab CI:

stages: [install, lint, test, build, deploy]

Step 4: Optimizations

Dependency caching (npm cache, pip cache, cargo cache)
Parallel test execution where possible
Matrix builds for multiple versions (if needed)
Fail-fast on lint errors (don't waste time on tests)
Artifact upload for build output

Rules

Always include a lint stage — catch issues early
Always include caching — speed up repeat runs
Keep the pipeline under 10 minutes for PRs
Don't hardcode versions — use variables or matrix
Include both push and PR triggers