zhangzhang-111-i/claude-skills111/ci-cd-pipeline-builder
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CI/CD Pipeline Builder
Install
npx vskill@latest install zhangzhang-111-i/claude-skills111/ci-cd-pipeline-builderSKILL.md
The same SKILL.md was published earlier as arnav-0/claude-code-setup/ci-cd-pipeline-builder.
CI/CD Pipeline Builder
Tier: POWERFUL Category: Engineering Domain: DevOps / Automation
Overview
Use this skill to generate pragmatic CI/CD pipelines from detected project stack signals, not guesswork. It focuses on fast baseline generation, repeatable checks, and environment-aware deployment stages.
Core Capabilities
- Detect language/runtime/tooling from repository files
- Recommend CI stages (
lint,test,build,deploy) - Generate GitHub Actions or GitLab CI starter pipelines
- Include caching and matrix strategy based on detected stack
- Emit machine-readable detection output for automation
- Keep pipeline logic aligned with project lockfiles and build commands
When to Use
- Bootstrapping CI for a new repository
- Replacing brittle copied pipeline files
- Migrating between GitHub Actions and GitLab CI
- Auditing whether pipeline steps match actual stack
- Creating a reproducible baseline before custom hardening
Key Workflows
1. Detect Stack
Supports input via stdin or --input file for offline analysis payloads.
2. Generate Pipeline From Detection
Or end-to-end from repo directly:
3. Validate Before Merge
- Confirm commands exist in project (
test,lint,build). - Run generated pipeline locally where possible.
- Ensure required secrets/env vars are documented.
- Keep deploy jobs gated by protected branches/environments.
4. Add Deployment Stages Safely
- Start with CI-only (
lint/test/build). - Add staging deploy with explicit environment context.
- Add production deploy with manual gate/approval.
- Keep rollout/rollback commands explicit and auditable.
Script Interfaces
python3 scripts/stack_detector.py --help- Detects stack signals from repository files
- Reads optional JSON input from stdin/
--input python3 scripts/pipeline_generator.py --help- Generates GitHub/GitLab YAML from detection payload
- Writes to stdout or
--output
Common Pitfalls
- Copying a Node pipeline into Python/Go repos
- Enabling deploy jobs before stable tests
- Forgetting dependency cache keys
- Running expensive matrix builds for every trivial branch
- Missing branch protections around prod deploy jobs
- Hardcoding secrets in YAML instead of CI secret stores
Best Practices
- Detect stack first, then generate pipeline.
- Keep generated baseline under version control.
- Add one optimization at a time (cache, matrix, split jobs).
- Require green CI before deployment jobs.
- Use protected environments for production credentials.
- Regenerate pipeline when stack changes significantly.
References
- references/github-actions-templates.md
- references/gitlab-ci-templates.md
- references/deployment-gates.md
- README.md
Detection Heuristics
The stack detector prioritizes deterministic file signals over heuristics:
- Lockfiles determine package manager preference
- Language manifests determine runtime families
- Script commands (if present) drive lint/test/build commands
- Missing scripts trigger conservative placeholder commands
Generation Strategy
Start with a minimal, reliable pipeline:
- Checkout and setup runtime
- Install dependencies with cache strategy
- Run lint, test, build in separate steps
- Publish artifacts only after passing checks
Then layer advanced behavior (matrix builds, security scans, deploy gates).
Platform Decision Notes
- GitHub Actions for tight GitHub ecosystem integration
- GitLab CI for integrated SCM + CI in self-hosted environments
- Keep one canonical pipeline source per repo to reduce drift
Validation Checklist
- Generated YAML parses successfully.
- All referenced commands exist in the repo.
- Cache strategy matches package manager.
- Required secrets are documented, not embedded.
- Branch/protected-environment rules match org policy.
Scaling Guidance
- Split long jobs by stage when runtime exceeds 10 minutes.
- Introduce test matrix only when compatibility truly requires it.
- Separate deploy jobs from CI jobs to keep feedback fast.
- Track pipeline duration and flakiness as first-class metrics.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingengineering/ci-cd-pipeline-builder/SKILL.md
Popularity
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