This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and generate CI/CD pipelines from project stack signals across GitHub Actions, GitLab CI, CircleCI, and Buildkite. Use when bootstrapping CI, migrating pipelines, adding deployment gates, or optimizing build times.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Generate production-grade CI/CD pipelines from detected project stack signals. Analyzes lockfiles, manifests, and scripts to produce optimized pipelines with proper caching, matrix strategies, security scanning, and deployment gates. Supports GitHub Actions, GitLab CI, CircleCI, and Buildkite with deployment strategies including blue-green, canary, and rolling updates.
Keywords: CI/CD, GitHub Actions, GitLab CI, pipeline, deployment, caching, matrix builds, blue-green deployment, canary deployment, security scanning, SAST, container builds, environment gates
Before generating the pipeline, confirm these inputs. If any is unknown or vague, ASK — do not assume:
pipeline_generator.py emits via --platform)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.
| Tool | Purpose | Command |
|---|---|---|
pipeline_generator.py | Generate pipeline YAML from project stack detection | python scripts/pipeline_generator.py . --platform github --deploy |
cache_optimizer.py | Analyze pipeline configs and suggest caching improvements | python scripts/cache_optimizer.py --dir . --severity high |
pipeline_linter.py | Lint pipeline YAML for common issues | python scripts/pipeline_linter.py --dir . --severity warning |
Load the reference that matches the task — keep this file lean and pull detail on demand:
This skill covers:
This skill does NOT cover:
engineering/saas-scaffolder)engineering/skill-security-auditor)engineering/observability-designer)engineering/migration-architect)| Skill | Integration | Data Flow |
|---|---|---|
engineering/dependency-auditor | Feeds vulnerability scan results into pipeline security gates | Auditor findings trigger pipeline failure or warning annotations |
engineering/release-manager | Coordinates versioning and changelog with deploy stages | Release tags drive conditional deployment job execution |
engineering/observability-designer | Post-deploy health checks and alerting complement pipeline gates | Pipeline triggers smoke tests; observability confirms deployment health |
engineering/env-secrets-manager | Manages secrets referenced by pipeline environment variables | Secret rotation policies feed into pipeline secret store configuration |
engineering/migration-architect | Database migrations run as a pre-deploy step in the pipeline | Migration status gates the application deployment job |
engineering/runbook-generator | Generates rollback runbooks aligned with deployment strategy | Pipeline failure triggers link to the relevant rollback runbook |
아직 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.
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.