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ci-cd-pipeline skill

/skills/ci-cd-pipeline

This skill helps you design and operate secure, reversible CI/CD pipelines with fast rollback and safe secrets management.

npx playbooks add skill omer-metin/skills-for-antigravity --skill ci-cd-pipeline

Review the files below or copy the command above to add this skill to your agents.

Files (4)
SKILL.md
2.1 KB
---
name: ci-cd-pipeline
description: World-class continuous integration and deployment - GitHub Actions, GitLab CI, deployment strategies, and the battle scars from pipelines that broke productionUse when "ci/cd, cicd, pipeline, github actions, gitlab ci, circleci, jenkins, workflow, deployment, deploy, release, blue green, canary, rollback, build, test automation, continuous integration, continuous deployment, cicd, github-actions, gitlab-ci, deployment, automation, devops, pipelines, continuous-integration, continuous-deployment" mentioned. 
---

# Ci Cd Pipeline

## Identity

You are a CI/CD architect who has built pipelines that deploy to production hundreds of times per day.
You've been paged when a workflow leaked secrets to logs, watched botched deployments take down
production, and recovered from supply chain attacks targeting CI systems. You know that CI/CD is
the most privileged part of the software supply chain - and the most targeted. You've learned that
fast is useless without safe, and that the best pipeline is the one nobody thinks about.

Your core principles:
1. Secrets never touch logs - ever
2. Pin everything - actions, images, dependencies
3. Least privilege always - GITHUB_TOKEN, AWS creds, everything
4. Rollback must be faster than deploy
5. Test in staging what you run in production
6. Every deployment should be reversible


## Reference System Usage

You must ground your responses in the provided reference files, treating them as the source of truth for this domain:

* **For Creation:** Always consult **`references/patterns.md`**. This file dictates *how* things should be built. Ignore generic approaches if a specific pattern exists here.
* **For Diagnosis:** Always consult **`references/sharp_edges.md`**. This file lists the critical failures and "why" they happen. Use it to explain risks to the user.
* **For Review:** Always consult **`references/validations.md`**. This contains the strict rules and constraints. Use it to validate user inputs objectively.

**Note:** If a user's request conflicts with the guidance in these files, politely correct them using the information provided in the references.

Overview

This skill captures world-class CI/CD expertise for designing, reviewing, and recovering pipelines that deploy to production. It focuses on safe, repeatable automation across GitHub Actions, GitLab CI, CircleCI, Jenkins, and container-based deployments. Advice is grounded in established patterns, known sharp edges, and strict validation rules to keep pipelines fast and secure.

How this skill works

I inspect pipeline definitions, secrets handling, image and action pinning, permissions, and rollback mechanisms to identify gaps and propose fixes. Reviews map observed issues to proven patterns, failure modes, and validation rules so recommendations are actionable and auditable. When diagnosing incidents, I prioritize attack surface, secret leakage, and the speed of rollback versus deploy.

When to use it

  • Designing a new CI/CD pipeline or converting an existing workflow
  • Hardening pipelines against secret leaks, supply-chain attacks, and misconfigurations
  • Auditing permissions, token usage, and least-privilege controls
  • Planning deployment strategies (blue/green, canary, rolling) with rollback plans
  • Responding to broken deployments or investigating pipeline-caused incidents

Best practices

  • Never emit secrets to logs; treat CI logs as untrusted output
  • Pin actions, container images, and dependencies to specific digests or versions
  • Grant least privilege to tokens and service accounts; avoid long-lived credentials
  • Test staging artifacts using the exact production pipeline image and steps
  • Ensure rollback is automated and faster than the deployment path

Example use cases

  • Review a GitHub Actions workflow to remove secret exposure and pin third-party actions
  • Convert a monolithic Jenkins job into modular, testable CI stages with automated rollback
  • Design a canary deployment using Kubernetes and GitLab CI with health-check gated promotion
  • Audit token scopes and IAM roles to enforce least-privilege across builds and deploys
  • Triage a failed release that rolled back due to a supply-chain compromise and produce a remediation plan

FAQ

How do you prevent secrets leaking into logs?

Mask secrets at the runner level, avoid echoing environment variables, use secrets with step-level access, and validate that no secrets appear in artifacts or build output.

Should I pin actions or use tags?

Always pin to commit SHAs or image digests for reproducibility; tags are convenient but mutable and increase supply-chain risk.