Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Implement Kubernetes security policies including NetworkPolicy, PodSecurityPolicy, and RBAC for production-grade security. Use when securing Kubernetes clusters, implementing network isolation, or enforcing pod security standards.
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Comprehensive guide for implementing NetworkPolicy, PodSecurityPolicy, RBAC, and Pod Security Standards in Kubernetes.
Implement defense-in-depth security for Kubernetes clusters using network policies, pod security standards, and RBAC.
apiVersion: v1
kind: Namespace
metadata:
name: privileged-ns
labels:
pod-security.kubernetes.io/enforce: privileged
pod-security.kubernetes.io/audit: privileged
pod-security.kubernetes.io/warn: privileged
apiVersion: v1
kind: Namespace
metadata:
name: baseline-ns
labels:
pod-security.kubernetes.io/enforce: baseline
pod-security.kubernetes.io/audit: baseline
pod-security.kubernetes.io/warn: baseline
apiVersion: v1
kind: Namespace
metadata:
name: restricted-ns
labels:
pod-security.kubernetes.io/enforce: restricted
pod-security.kubernetes.io/audit: restricted
pod-security.kubernetes.io/warn: restricted
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: default-deny-all
namespace: production
spec:
podSelector: {}
policyTypes:
- Ingress
- Egress
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: allow-frontend-to-backend
namespace: production
spec:
podSelector:
matchLabels:
app: backend
policyTypes:
- Ingress
ingress:
- from:
- podSelector:
matchLabels:
app: frontend
ports:
- protocol: TCP
port: 8080
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: allow-dns
namespace: production
spec:
podSelector: {}
policyTypes:
- Egress
egress:
- to:
- namespaceSelector:
matchLabels:
name: kube-system
ports:
- protocol: UDP
port: 53
Reference: See assets/network-policy-template.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: pod-reader
namespace: production
rules:
- apiGroups: ['']
resources: ['pods']
verbs: ['get', 'watch', 'list']
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: secret-reader
rules:
- apiGroups: ['']
resources: ['secrets']
verbs: ['get', 'watch', 'list']
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: read-pods
namespace: production
subjects:
- kind: User
name: jane
apiGroup: rbac.authorization.k8s.io
- kind: ServiceAccount
name: default
namespace: production
roleRef:
kind: Role
name: pod-reader
apiGroup: rbac.authorization.k8s.io
Reference: See references/rbac-patterns.md
apiVersion: v1
kind: Pod
metadata:
name: secure-pod
spec:
securityContext:
runAsNonRoot: true
runAsUser: 1000
fsGroup: 1000
seccompProfile:
type: RuntimeDefault
containers:
- name: app
image: myapp:1.0
securityContext:
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop:
- ALL
apiVersion: templates.gatekeeper.sh/v1
kind: ConstraintTemplate
metadata:
name: k8srequiredlabels
spec:
crd:
spec:
names:
kind: K8sRequiredLabels
validation:
openAPIV3Schema:
type: object
properties:
labels:
type: array
items:
type: string
targets:
- target: admission.k8s.gatekeeper.sh
rego: |
package k8srequiredlabels
violation[{"msg": msg, "details": {"missing_labels": missing}}] {
provided := {label | input.review.object.metadata.labels[label]}
required := {label | label := input.parameters.labels[_]}
missing := required - provided
count(missing) > 0
msg := sprintf("missing required labels: %v", [missing])
}
apiVersion: constraints.gatekeeper.sh/v1beta1
kind: K8sRequiredLabels
metadata:
name: require-app-label
spec:
match:
kinds:
- apiGroups: ['apps']
kinds: ['Deployment']
parameters:
labels: ['app', 'environment']
apiVersion: security.istio.io/v1beta1
kind: PeerAuthentication
metadata:
name: default
namespace: production
spec:
mtls:
mode: STRICT
apiVersion: security.istio.io/v1beta1
kind: AuthorizationPolicy
metadata:
name: allow-frontend
namespace: production
spec:
selector:
matchLabels:
app: backend
action: ALLOW
rules:
- from:
- source:
principals: ['cluster.local/ns/production/sa/frontend']
NetworkPolicy not working:
# Check if CNI supports NetworkPolicy
kubectl get nodes -o wide
kubectl describe networkpolicy <name>
RBAC permission denied:
# Check effective permissions
kubectl auth can-i list pods --as system:serviceaccount:default:my-sa
kubectl auth can-i '*' '*' --as system:serviceaccount:default:my-sa
assets/network-policy-template.yaml - Network policy examplesassets/pod-security-template.yaml - Pod security policiesreferences/rbac-patterns.md - RBAC configuration patternsk8s-manifest-generator - For creating secure manifestsgitops-workflow - For automated policy deploymentBefore starting:
cat C:\dev\projects\agent-studio\.claude\context\memory\learnings.md
After completing:
C:\dev\projects\agent-studio\.claude\context\memory\learnings.mdC:\dev\projects\agent-studio\.claude\context\memory\issues.mdC:\dev\projects\agent-studio\.claude\context\memory\decisions.mdASSUME INTERRUPTION: If it's not in memory, it didn't happen.
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Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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