Agent skill · software engineering · borghei
devops-workflow-engineer
Generate and optimize GitHub Actions CI/CD workflows. Use when designing workflows, planning multi-environment deployments, optimizing pipeline cost and runtime, or implementing blue- green, canary, or rolling deployment strategies.
Why this skill is useful
Adds 3 executable scripts for generating, analyzing, and planning GitHub Actions workflows that extend the AI's capabilities in CI/CD.
What it needs
Requires python installed locally. About 2k tokens when loaded. Last updated 2026-07-21. 462 stars on the source repository.
What this skill does
DevOps Workflow Engineer Generate GitHub Actions workflow YAML, analyze existing pipelines for optimization opportunities, and create deployment plans with strategy selection, health checks, and rollback procedures. Core Capabilities CI pipeline design — fail-fast job ordering (lint → unit → build → integration → security) with matrix testing and CI time/flake/cache targets. CD & multi-environment — dev/staging/prod promotion flows, build-once-deploy-everywhere, environment protection rules, and rollback at every stage. Pipeline optimization — detect missing caching, missing timeouts, serial chains, deprecated actions, leaked secrets, and oversized runners; apply path filtering and concurrency cancellation. Deployment strategies — choose blue-green, canary, or rolling via decision tree; canary traffic-split schedule with promotion gates. GitHub Actions patterns — reusable workflows, OIDC auth, secrets hierarchy, and runner cost estimation. When to Use Designing a new CI or CD workflow from scratch. Planning a multi-environment (dev/staging/prod) deployment. Optimizing an existing pipeline's cost or runtime. Implementing a blue-green, canary, or rolling deployment strategy. Clarify First Before generating the workflow, confirm these inputs. If any is unknown or vague, ASK — do not assume: [ ] Workflow type — CI, CD, release, or security-scan (sets workflowgenerator.py --type) [ ] Stack — language and test framework (e.g. python/pytest) (drives the generated YAML steps via --language/--test-framework) [ ] Deployment strategy & environments — blue-green, canary, or rolling, and which of dev/staging/prod (drives the deploymentplanner.py plan) Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills borghei/devops-workflow-engineer