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Found 528 Skills
Use this skill to work with Microsoft Foundry (Azure AI Foundry): deploy AI models from catalog, build RAG applications with knowledge indexes, create and evaluate AI agents, manage RBAC permissions and role assignments, manage quotas and capacity, create Foundry resources. USE FOR: Microsoft Foundry, AI Foundry, deploy model, model catalog, RAG, knowledge index, create agent, evaluate agent, agent monitoring, create Foundry project, new Foundry project, set up Foundry, onboard to Foundry, provision Foundry infrastructure, create Foundry resource, create AI Services, multi-service resource, AIServices kind, register resource provider, enable Cognitive Services, setup AI Services account, create resource group for Foundry, RBAC, role assignment, managed identity, service principal, permissions, quota, capacity, TPM, deployment failure, QuotaExceeded. DO NOT USE FOR: Azure Functions (use azure-functions), App Service (use azure-create-app), generic Azure resource creation (use azure-create-app).
Design comprehensive testing strategies for software quality assurance. Use when planning test coverage, implementing test pyramids, or setting up testing infrastructure. Handles unit testing, integration testing, E2E testing, TDD, and testing best practices.
Automate application deployment to cloud platforms and servers. Use when setting up CI/CD pipelines, deploying to Docker/Kubernetes, or configuring cloud infrastructure. Handles GitHub Actions, Docker, Kubernetes, AWS, Vercel, and deployment best practices.
Set up monitoring, logging, and observability for applications and infrastructure. Use when implementing health checks, metrics collection, log aggregation, or alerting systems. Handles Prometheus, Grafana, ELK Stack, Datadog, and monitoring best practices.
Configure development and production environments for consistent and reproducible setups. Use when setting up new projects, Docker environments, or development tooling. Handles Docker Compose, .env configuration, dev containers, and infrastructure as code.
Performs comprehensive preflight validation of Bicep deployments to Azure, including template syntax validation, what-if analysis, and permission checks. Use this skill before any deployment to Azure to preview changes, identify potential issues, and ensure the deployment will succeed. Activate when users mention deploying to Azure, validating Bicep files, checking deployment permissions, previewing infrastructure changes, running what-if, or preparing for azd provision.
Create a new implementation plan file for new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
Update an existing implementation plan file with new or update requirements to provide new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
Implement comprehensive testing strategies using Jest, Vitest, and Testing Library for unit tests, integration tests, and end-to-end testing with mocking, fixtures, and test-driven development. Use when writing JavaScript/TypeScript tests, setting up test infrastructure, or implementing TDD/BDD workflows.
Agent onboarding for Orderly Network - omnichain perpetual futures infrastructure, MCP server, skills, and developer quickstart
Build applications with InsForge Backend-as-a-Service. Use when developers need to: (1) Set up backend infrastructure (create tables, storage buckets, deploy functions, configure auth/AI) (2) Integrate InsForge SDK into frontend applications (database CRUD, auth flows, file uploads, AI operations, real-time messaging) (3) Deploy frontend applications to InsForge hosting IMPORTANT: Before any backend work, you MUST have the user's Project URL and API Key. If not provided, ask the user first. Key distinction: Backend configuration uses HTTP API calls to the InsForge project URL. Client integration uses the @insforge/sdk in application code.
Forces exhaustive problem-solving using corporate PUA rhetoric and structured debugging methodology. MUST trigger when: (1) any task has failed 2+ times or you're stuck in a loop tweaking the same approach; (2) you're about to say 'I cannot', suggest the user do something manually, or blame the environment without verifying; (3) you catch yourself being passive — not searching, not reading source, not verifying, just waiting for instructions; (4) user expresses frustration in ANY form: 'try harder', 'stop giving up', 'figure it out', 'why isn't this working', 'again???', '换个方法', '为什么还不行', '你再试试', '加油', '你怎么又失败了', or any similar sentiment even if phrased differently. Also trigger when facing complex multi-step debugging, environment issues, config problems, or deployment failures where giving up early is tempting. Applies to ALL task types: code, config, research, writing, deployment, infrastructure, API integration. Do NOT trigger on first-attempt failures or when a known fix is already executing successfully.