Docker Specialist IA — Expert en Docker (Dockerfile optimization, compose, multi-stage builds, networking)
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Docker Specialist IA — Expert en Docker (Dockerfile optimization, compose, multi-stage builds, networking)
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Docker (Docker Engine / Dockerfile / Compose / Buildx) の Dockerfile 命令, docker CLI, compose.yaml (Compose Specification), BuildKit, Bake (HCL), マルチステージ, マルチプラットフォーム, ビルドキャッシュ, SBOM / provenance, dockerd, daemon.json, logging driver, rootless, seccomp。
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Dockerfile, multi-stage build, Compose, buildx, registry, otimização e segurança de imagem. Use quando o usuário disser "docker", "dockerfile", "imagem", "container", "build", "compose", "imagem muito grande", "trivy", "vulnerabilidade na imagem".
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Use when optimizing Docker builds with BuildKit, designing multi-stage Dockerfiles, leveraging cache mounts, building multi-arch images, choosing distroless vs alpine, or signing images with cosign. Triggers: docker build slow, layer cache not hitting, npm install / pip install reruns, multi-stage final image bloat, glibc vs musl issues, RUN --mount=type=cache, BUILDKIT_INLINE_CACHE, registry cache exporters, qemu emulation for arm64, COPY ordering for cache. NOT for Docker daemon admin, Kubernetes-specific image policies, container security scanning workflows, or Buildpacks (different paradigm).
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Create optimized multi-stage Dockerfiles for any language or framework
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Containerize an ASP.NET Core project by creating Dockerfile and .dockerfile files customized for the project.
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Containerize an ASP.NET .NET Framework project by creating Dockerfile and .dockerfile files customized for the project.
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Convert existing scripts, CLI tools, or Crawlee projects into reusable Apify Actors, programs packaged as Docker images. Define JSON inputs and outputs, integrate the SDK, test locally, and deploy to Apify.
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Extend a NanoClaw agent's own environment with packages, external tools, or specialist agents. The skill chooses the workflow for each change, edits memory and standing instructions, and delegates source changes to a builder for review.
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Add persistent memory to NanoClaw agents using the default Claude provider. With mnemon installed in the container, agents retrieve relevant context before responding and save new insights after each turn, retaining memory across container restarts.
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Review a NemoClaw pull request for security risks by examining changed code, configuration, and dependencies. Assess nine categories and report findings with severity, file locations, and recommended fixes, alongside an overall assessment of whether it is safe to merge.
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Publish a built website or web app and provide a shareable URL through Kortix Apps, Cloudflare, or Vercel. Check the running build, security, external service requirements, and data storage limits before deploying with the user's explicit approval.
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Build and operate websites, internal tools, APIs, and databases on Kortix Apps using its CLI or SDK. Covers deployment, sign-in, scaling, persistent storage that survives updates, snapshots, and restoring earlier application releases.
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Review source code, dependencies, and infrastructure settings for security issues. Find exposed credentials, unsafe input handling, and access control gaps, then organize findings into a report with severity levels, affected locations, and recommended fixes.
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Guides fuzz testing for Ruby libraries and gems with Ruzzy, using varied inputs to find failures. Covers pure Ruby and C extensions, including test harnesses, memory error detection, environment setup, and crash reproduction.
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Create an isolated development container configured for Claude Code and the project's languages. Generate container files, editor settings, dependency setup commands, and persistent storage for Python, Node/TypeScript, Rust, and Go projects.
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Assess Docker, containerd, and Podman environments for weaknesses that could expose the host system. The skill organizes checks for excessive permissions, exposed runtime sockets, and known vulnerabilities, alongside indicators defenders can monitor.
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Create starter projects for AI agents, add deployment configuration and automated build and release pipelines to existing projects, or update generated project files. Supports Python and Go ADK templates and a prototype-first approach.
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Prepare an existing OpenClaw setup for import as an AgentTeams managed Worker. Analyze tool dependencies, adapt role instructions and scheduled jobs, and build a ZIP package containing the configuration and custom image requirements.
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DOCA Flow packet steering on NVIDIA NICs/DPUs, linked into a C application: match/action pipes, ports, representors, forwarding, hairpin, counters. Trigger on packet steering, classifier, rule-matching, representor, hairpin or 5-tuple-to-queue questions even when "DOCA Flow" is not named. Remote or non-C++ control over gRPC belongs to doca-flow-grpc-server. Also covers pipe validation before hardware programming, Flow/DOCA version match, and Flow API errors. First app: follow the local bundle (doca-setup, doca-programming-guide, doca-flow, doca-public-knowledge-map). Stage 1 pull nvcr.io/nvidia/doca/doca (NGC catalog tag, never invent); Stage 2 needs a real NIC. Then ls samples inside the container; never emit main.c, a Dockerfile, or hand-typed -l flags. Route software-only host pipelines, plain DPDK `rte_flow`, kernel TC, OVS, BFB bring-up, and DPU OS installation elsewhere. DPU OS installation is destructive and always requires explicit confirmation.
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Bootstrap the KERMT agent environment — verify host docker + nvidia-container-toolkit, build the kermt:latest image from the repo's Dockerfile if it doesn't yet exist, and run a GPU smoke test inside the container. Every other kermt-* skill depends on this; invoke it first.
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Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.
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Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
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Assess whether source code is ready to deploy to Azure — the check BEFORE infrastructure work. Evaluates build health, app completeness, dependencies and local services, stack compatibility, and deployment feasibility. Answers questions about what your app needs before it can be deployed — frameworks, dependencies, and configuration. Checks whether dependencies are compatible and identifies deployment blockers and unsupported frameworks. WHEN: "evaluate my repo", "is my app ready to deploy", "what does my app need to deploy", "what do I need before deploying", "does my app need", "can I ship this to Azure", "scan my repo for issues", "is this app deployable", "check if my app is ready for Azure", "do I need a Dockerfile", "what's blocking my deployment", "are there any blockers", "are my dependencies compatible", "does Azure support my framework", "what needs to change before deploying", "check my app configuration".
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