Find the perfect capability for your agent.
Upgrades Go version across the entire Chainloop codebase including source files, Docker images, CI/CD workflows, and documentation. Use when the user mentions upgrading Go, golang version, or updating Go compiler version.
Docker and OCI container image expertise for building, optimizing, and securing container images
Assist in containerizing applications with Dockerfile generation and optimization
Docker containerization for web apps, multi-stage builds, and optimization.
Docker-based test environment management for isolated, reproducible test execution. Create Docker Compose environments, manage test containers, configure service dependencies, and integrate with CI/CD pipelines.
Skills for using Docker Model Runner to run local LLM inference
Import Docker Compose files into Kurtosis. Convert docker-compose.yml to Starlark packages or run them directly. Use when migrating existing Docker Compose workflows to Kurtosis.
Build, push, and deploy Kurtosis dev images to a Kubernetes cluster without creating a release. Rebuilds engine, core, and files-artifacts-expander as multi-arch Docker images with a unique tag, pushes to the logged-in user's Docker Hub, and restarts the engine. Use when testing local code changes on a k8s cluster.
Build and test Kurtosis from source on local Docker. Compiles all components (engine, core, files-artifacts-expander), builds Docker images, installs the CLI, and restarts the engine. Use when developing Kurtosis and testing changes locally with Docker.
Build and test the Kurtosis CLI from source. Compile the CLI binary locally, run it against Docker or Kubernetes engines, and iterate on CLI changes without creating a release. Use when developing or debugging CLI commands.
Railway container deployment specialist covering Docker, multi-service architectures, persistent volumes, and auto-scaling. Use when deploying containerized full-stack applications, configuring multi-region deployments, or setting up persistent storage.
Транспиляция ES6+ JavaScript в ES5 для совместимости с браузерами используя Docker-based Babel компилятор. Использовать при транспиляции JavaScript файлов после внесения изменений в ES6+ исходный код.
Анализ логов Docker контейнера для диагностики проблем и мониторинга здоровья системы. Использовать при отладке ошибок, отслеживании процессов воркеров, исследовании проблем API или мониторинге поведения системы после тестов.
Универсальный REST API клиент для MikoPBX с автоматической аутентификацией и выполнением запросов внутри Docker контейнеров. Использовать когда нужно тестировать API эндпоинты, выполнять CRUD операции (GET, POST, PATCH, DELETE) или отлаживать API ответы с конкретными параметрами.
Zero Script QA — test without scripts using structured JSON logging and Docker monitoring. Triggers: zero-script-qa, log testing, docker logs, QA, 제로 스크립트 QA.
Expert knowledge for Azure AI Content Safety development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Content Safety APIs, Docker containers, blocklists, groundedness checks, or custom safety categories, and other Azure AI Content Safety related development tasks. Not for Azure Information Protection (use azure-information-protection), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel), Azure Defender For Cloud (use azure-defender-for-cloud).
Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. Use when using univariate/multivariate APIs, Docker/IoT Edge containers, predictive maintenance flows, or regional limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
Expert knowledge for Azure AI Document Intelligence development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using AnalyzeDocument/Markdown APIs, custom models, containers/Docker, SAS/managed identity, or VNets, and other Azure AI Document Intelligence related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure AI Search (use azure-cognitive-search), Azure AI Language (use azure-language-service), Azure AI Immersive Reader (use azure-immersive-reader).
