access-review
FreeConduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
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Secure Docker images and container runtime configurations. Implement non-root users, read-only filesystems, and security contexts. Use when building secure container images or hardening container deployments.
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See how to installReview the instructions the agent will receive before you install.
Secure container images and runtime configurations.
Use this skill when:
# Use minimal base image
FROM alpine:3.18
# Don't run as root
RUN addgroup -g 1001 -S appgroup && \
adduser -u 1001 -S appuser -G appgroup
# Copy with specific ownership
COPY --chown=appuser:appgroup . /app
# Remove unnecessary packages
RUN apk del --purge build-dependencies && \
rm -rf /var/cache/apk/*
# Use non-root user
USER appuser
# Read-only filesystem support
WORKDIR /app
# Run with security options
docker run -d \
--read-only \
--tmpfs /tmp \
--security-opt=no-new-privileges:true \
--cap-drop=ALL \
--cap-add=NET_BIND_SERVICE \
--user 1001:1001 \
myapp:latest
apiVersion: v1
kind: Pod
spec:
securityContext:
runAsNonRoot: true
runAsUser: 1001
fsGroup: 1001
containers:
- name: app
securityContext:
allowPrivilegeEscalation: false
readOnlyRootFilesystem: true
capabilities:
drop: ["ALL"]
# Scan with Trivy
trivy image --severity HIGH,CRITICAL myapp:latest
# Use distroless images
FROM gcr.io/distroless/static-debian11
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Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
The English summary is being prepared. Showing the original description.
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
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Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
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Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
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Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
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Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
The English summary is being prepared. Showing the original description.