analyzing-docker-container-forensics
Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.
Trouvez la capacité idéale pour votre agent.
Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.
Harden the Docker daemon by configuring daemon.json with user namespace remapping, TLS authentication, rootless mode, and CIS benchmark controls.
Create or update a Sublime Text 3 compatible `.sublime-syntax` grammar in the repository `syntaxes/` directory when asked for a specific language or format such as JSON, TypeScript, Elm, or Dockerfile.
Docker and container development agent skill and plugin for Dockerfile optimization, docker-compose orchestration, multi-stage builds, and container security hardening. Use when: user wants to optimize a Dockerfile, create or improve docker-compose configurations, implement multi-stage builds, audit container security, reduce image size, or follow container best practices. Covers build performance, layer caching, secret management, and production-ready container patterns.
Spawn a new OpenClaw agent through conversation. Uses official Docker setup and non-interactive onboarding, carries over API keys, tools, plugins, and skills from the current agent. User answers 2-3 questions. Use when the user wants to create, spin up, deploy, or provision a new OpenClaw agent.
Design, configure, debug, and optimize OpenClaw AI agent deployments. Master guide for gateway configuration, openclaw.json settings, model routing and fallback chains, skills development and publishing, cron job scheduling, memory systems (Qdrant, Neo4j, SQLite), Docker infrastructure, and Tailscale VPN networking. Includes config analyzer that audits your openclaw.json and suggests improvements, plus health checker that validates all OpenClaw subsystems. Built for AI agents — Python stdlib only, no dependencies. Use for OpenClaw setup, gateway debugging, skill building, cron management, model optimization, cost reduction, and infrastructure troubleshooting.
ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization. Use when the user asks about deploying ML models to production, setting up MLOps infrastructure (MLflow, Kubeflow, Kubernetes, Docker), monitoring model performance or drift, building RAG pipelines, or integrating LLM APIs with retry logic and cost controls. Focused on production and operational concerns rather than model research or initial training.
OpenClaw self-hosted AI agent framework expert. Trigger for: openclaw.json, gateway, channels, models, skills, agents, secrets, cron, sandbox, memory, multi-agent, bindings, dmPolicy, SecretRef, session config, workspace files (AGENTS.md, SOUL.md, MEMORY.md), troubleshooting, security hardening. Covers installation, configuration, channel setup, memory tuning, Docker deployment.
Autonomous multi-agent code generation. Planner creates manifest, specialized roles execute tasks. Generates complete projects with tests, Docker, CI, and decision logs.
Expert Senior Django Architect specializing in high-performance, containerized, async-capable architectures. Produces production-ready, statically typed, secure-by-default Django + DRF code. Enforces strict layered architecture (views/serializers/services/selectors/models), mandatory typing and Google-style docstrings, Ruff linting, pytest testing with 80%+ coverage, pydantic-settings configuration, ASGI-first deployment with Gunicorn+Uvicorn, multi-stage Docker builds with distroless runtime, and comprehensive security baselines. All code must be complete with zero placeholders.
Use for Dokploy-specific API operations (apps, deployments, databases, domains, backups, settings) when tasks explicitly involve Dokploy. Route requests to domain modules, enforce inspect-first troubleshooting and controlled mutations via x-api-key authentication, and avoid use for generic Docker/Kubernetes work outside Dokploy.
Run the Model Context Protocol (MCP) Atlassian server in Docker, enabling integration with Jira, Confluence, and other Atlassian products. Use when you need to query Jira issues, search Confluence, or interact with Atlassian services programmatically. Requires Docker and valid Jira API credentials.
This is my personal template collection. Here you'll find templates, and configurations for various boilerplates, python, ansible, docker, docker-compose, kubernetes, packer. Use when you need boilerplates capabilities. Triggers on: boilerplates.
Deploy any project to xCloud hosting — auto-detects stack (WordPress, Laravel, PHP, Node.js, Next.js, NestJS, Python, Go, Rust), routes to native or Docker deployment, generates production-ready Dockerfile, docker-compose.yml, GitHub Actions CI/CD, and .env.example. Works from zero Docker setup.
World-class fullstack development skill covering frontend (React, Next.js, Vue, HTML/CSS/JS), backend (Node.js, Python/FastAPI, Django, Express), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL), DevOps (Docker, CI/CD), and architecture design. Use this skill whenever the user asks to build, fix, review, architect, or debug ANY web application — frontend, backend, or full-stack.
Production-ready vLLM deployment on AMD ROCm GPUs. Combines environment auto-check, model parameter detection, Docker Compose deployment, health verification, and functional testing with comprehensive logging and security best practices.
智能部署工具 - 自动检测部署策略,预检查、发布、监控一体化。支持 K8s/Helm、Docker Compose、Vercel、Fly.io。Triggers: '部署', 'deploy', '发布', '上线', '预检查', '部署监控', 'helm upgrade', 'docker compose up'.
Essential Docker commands and workflows for container management, image operations, and debugging.