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, build, and operate Kubernetes operators. Use when extending Kubernetes with a custom controller, choosing a framework, designing CRDs, implementing reconciliation loops, or auditing an operator for anti-patterns.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
End-to-end Kubernetes operator design and construction. Covers the operator pattern (control loops for stateful workloads), CRD design (schema, validation, conversion, status), the reconciliation loop (idempotency, convergence, level- vs edge-triggered), framework selection (controller-runtime / Kubebuilder / operator-SDK / metacontroller), and operational concerns (finalizers, leader election, RBAC scoping, status subresource, observability). Targets Go-based operators (the dominant ecosystem) with notes on alternatives (KOPF, JOSDK, kube-rs).
| Situation | Skill applies |
|---|---|
| Building a new operator for an internal platform primitive | Yes — start with the operator pattern decision |
| Auditing an existing operator for production-readiness | Yes — use anti-patterns + scripts/reconciliation_audit.py |
| Designing CRDs for a custom resource | Yes — use CRD design + scripts/crd_validator.py |
| Deciding "operator vs Helm chart vs plain manifests" | Yes — use the decision matrix |
| Scaffolding a new operator project | Yes — scripts/operator_scaffold.py |
| Debugging a controller that "isn't reconciling" | Yes — use reconciliation troubleshooting |
| Just running someone else's operator (Postgres, Kafka, etc.) | Partially — useful for understanding what it does and how to monitor it |
Before scaffolding or auditing, confirm these inputs. If any is unknown or vague, ASK — do not assume:
operator_scaffold.py vs crd_validator.py vs reconciliation_audit.py)--name/--group/--kind); for validation/audit: the CRD YAML or controller path (the input the scripts read)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 |
|---|---|---|
crd_validator.py | Validate CRD YAML against design best practices (preserve-unknown, missing descriptions/enums/printer-columns, status subresource, cluster-scope) | python3 scripts/crd_validator.py --schema my-crd.yaml --format markdown |
operator_scaffold.py | Generate a production-ready operator project skeleton with stricter RBAC, observability, and finalizer scaffolding | python3 scripts/operator_scaffold.py --name db-operator --group example.com --kind Database |
reconciliation_audit.py | Audit Go controller source + CRDs for static-detectable anti-patterns (missing finalizers, no leader election, tight loops, no ownerRef, wide RBAC) | python3 scripts/reconciliation_audit.py --controller-path ./internal/controllers --crd ./config/crd/bases/*.yaml |
All scripts: stdlib only, argparse CLI, JSON or markdown output.
Load the reference that matches the task — keep this file lean and pull detail on demand:
Covers: operator pattern decisions; CRD design (schema/validation/versioning/conversion/subresources); idempotent reconciliation loops; Go controller-runtime / Kubebuilder / operator-SDK patterns; finalizers, leader election, RBAC scoping, observability; anti-pattern auditing. Primary target is Go operators, with notes on KOPF (Python), JOSDK (Java), kube-rs (Rust).
Does NOT cover: operating third-party community operators beyond understanding/monitoring them; cloud-provider-specific resource provisioning (see Crossplane); general Kubernetes cluster administration.
| Skill | Integration |
|---|---|
engineering/chaos-engineering | Chaos-test operators (kill the controller, partition from API server) |
engineering/observability-designer | Wire metrics + logging for operators |
engineering/incident-commander | Operators amplify blast radius; incident response matters more |
engineering/feature-flags-architect | Operators with spec.feature.<x>.enabled fields effectively become flag systems; consider the trade-off |
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 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.
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.
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.