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modal-master
Manage Modal.com serverless cloud platform: deploy GPU-accelerated Python functions, configure autoscaling and scheduling, build web endpoints with FastAPI, and debug production issues.
Manage Modal.com serverless cloud platform: deploy GPU-accelerated Python functions, configure autoscaling and scheduling, build web endpoints with FastAPI, and debug production issues.
Debug Modal issues including container failures, GPU errors, and deployment problems
Deploy a Modal application with environment configuration and CI/CD setup
Configure GPU functions with optimal settings, fallbacks, and cost optimization
Set up scheduled and cron functions with timezone support
Initialize a Modal project with proper structure, configuration, and best practices
Uses power tools
Uses Bash, Write, or Edit tools
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
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npx claudepluginhub josiahsiegel/claude-plugin-marketplace --plugin modal-masterComplete Azure cloud expertise covering 2025-2026 features. This plugin should be used for ANY Azure resource provisioning, AKS Automatic, Container Apps GPU, Azure OpenAI (GPT-5, reasoning models), Deployment Stacks, Azure ML workspaces, AI Foundry, compute clusters, endpoints, Terraform, networking, private endpoints, managed identities, debugging, and cost optimization.
JosiahSiegelDeploy ML models with FastAPI, Docker, Kubernetes. Use for serving predictions, containerization, monitoring, drift detection, or encountering latency issues, health check failures, version conflicts.
secondskyUse this agent when setting up CI/CD pipelines, configuring Docker containers, deploying applications to cloud platforms, setting up Kubernetes clusters, implementing infrastructure as code, or automating deployment workflows. Examples: <example>Context: User is setting up a new project and needs deployment automation. user: "I've built a FastAPI application and need to deploy it to production with proper CI/CD" assistant: "I'll use the deployment-engineer agent to set up a complete deployment pipeline with Docker, GitHub Actions, and production-ready configurations."</example> <example>Context: User mentions containerization or deployment issues. user: "Our deployment process is manual and error-prone. We need to automate it." assistant: "Let me use the deployment-engineer agent to design an automated CI/CD pipeline that eliminates manual steps and ensures reliable deployments."</example>
devsforgeDigitalOcean cloud deployment plugin for App Platform, Droplets, Kubernetes, Functions, Managed Databases, Spaces storage, and infrastructure management with official MCP server integration
vanman2024Google Cloud Platform service configuration and deployment
rohitg00Editorial "Azure AI & Cloud" bundle for Claude Code from Antigravity Awesome Skills.
sickn33Complete PowerShell 7.5/7.6 expertise system across ALL platforms (Windows/Linux/macOS) with 2025 breaking changes coverage, shell detection, and modern automation. PROACTIVELY activate for: (1) ANY PowerShell task (scripts/modules/cmdlets), (2) PowerShell 7.5.4 stable features (ConvertTo-CliXml, Test-Path -OlderThan/-NewerThan, .NET 9), (3) PowerShell 7.6 preview features (+= 16x optimization, Get-Clipboard -Delimiter, Get-Command -ExcludeModule, DSC v3, .NET 10), (4) 2025 migrations (MSOnline/AzureAD retirement, PowerShell 2.0 removal, WMIC replacement), (5) Modern security (SecretManagement, JEA, WDAC, Constrained Language Mode), (6) PSResourceGet 1.1.1/1.2.0 package management (2x faster than PowerShellGet), (7) CI/CD automation (GitHub Actions/Azure DevOps/GitLab), (8) Azure Az and Microsoft.Graph automation, (9) Cross-platform scripting with .NET 9/10 performance, (10) Shell detection and cross-shell compatibility (PowerShell vs Git Bash/MSYS2). Provides: PowerShell 7.5.4 stable / 7.6.0-preview.6 features, 2025 breaking changes guidance, MSOnline/AzureAD to Microsoft.Graph migration paths, WMIC to Get-CimInstance conversions, PSResourceGet adoption patterns, SecretManagement vault setup, Pester testing with coverage, module development best practices, latest security patterns (JEA, WDAC), shell detection on Windows, and production-ready 2025-2026 automation patterns.
JosiahSiegelComprehensive Python 3.13+ expertise system covering modern Python development, async programming, type hints, performance optimization, Modal.com serverless, OpenCV computer vision, FFmpeg video/audio processing, video pipeline integration, and cloud deployment. PROACTIVELY activate for: (1) ANY Python task, (2) Python 3.13+ features (free-threading, JIT), (3) asyncio and concurrent programming, (4) Type hints and mypy/pyright, (5) Package management (uv, pip, poetry), (6) Project structure (src layout, pyproject.toml), (7) FastAPI and web development, (8) Pydantic data validation, (9) Testing (pytest, coverage), (10) Cloudflare Workers/Containers Python, (11) GitHub Actions Python workflows, (12) Performance optimization and profiling, (13) Security best practices (OWASP), (14) Ruff linting and formatting, (15) Modal.com serverless functions and GPU workloads, (16) Modal scheduled tasks and cron jobs, (17) Modal parallel processing with map/starmap, (18) OpenCV image/video processing, (19) cv2.imread cv2.VideoCapture BGR color format, (20) Computer vision contours edge detection, (21) OpenCV DNN deep learning inference, (22) FFmpeg video encoding H.264 H.265 VP9 AV1, (23) ffmpeg-python filter graphs audio extraction, (24) PyAV frame-level video processing, (25) Video transcoding CRF presets hardware acceleration, (26) Audio conversion MP3 AAC FLAC Opus, (27) HLS DASH RTMP streaming protocols, (28) Video thumbnails GIF creation concatenation, (29) Subprocess FFmpeg deadlock prevention, (30) FFmpeg OpenCV integration pipeline, (31) Modal video processing parallel map starmap, (32) ffmpegcv GPU video reader writer, (33) VidGear RTSP streaming camera capture, (34) Decord batch video loading deep learning, (35) Video chunk parallel processing serverless, (36) BGR RGB color format conversion gotchas, (37) Frame dimension HWC CHW numpy transpose. Provides: Python 3.13 free-threading and JIT, asyncio patterns, comprehensive type hints, uv package management, FastAPI production patterns, Pydantic vs dataclass guidance, pytest testing, Cloudflare Python optimization, GitHub Actions caching, memory profiling, security hardening, Modal.com type-safe functions and ML inference patterns, OpenCV BGR/RGB conversion gotchas, video capture memory management, image filtering and transformations, feature detection and matching, DNN module inference, FFmpeg audio stream preservation gotchas, CRF encoding quality control, hardware acceleration NVENC QSV VAAPI, ffprobe metadata extraction, video filter chains, FFmpeg+OpenCV+Modal integration patterns, parallel frame processing with Modal map/starmap, GPU-accelerated video pipelines, chunk-based large video processing, HLS streaming generation on Modal.
JosiahSiegelUniversal context management and planning system. PROACTIVELY activate for: (1) ANY complex task requiring planning, (2) Multi-file projects/websites/apps, (3) Architecture decisions, (4) Research tasks, (5) Refactoring, (6) Long coding sessions, (7) Tasks with 3+ sequential steps. Provides: optimal file creation order, context-efficient workflows, extended thinking delegation (23x context efficiency), Claude Sonnet 4.5 token budgeting, recursive delegation patterns, clear-and-verify production workflows, passive deep analysis architecture, progressive task decomposition, cross-platform Windows/Git Bash support, and prevents redundant work. Saves 62% context on average. Essential for maintaining session performance and analytical depth.
JosiahSiegelComplete Salesforce expertise system across ALL platforms and integration scenarios with Windows/Git Bash compatibility. PROACTIVELY activate for: (1) ANY Salesforce task (API/data/Apex/Lightning/Flow), (2) SOQL/SOSL query design and optimization, (3) REST/SOAP API integration and authentication, (4) Apex development (classes/triggers/batch/scheduled) with Spring '25 features, (5) Lightning Web Components with lightning/graphql module and Aura development, (6) Data model design and schema management (objects/fields/relationships), (7) Integration patterns (source-to-Salesforce, Salesforce-to-target), (8) Deployment and metadata management (change sets/SFDX/CLI) with Windows/Git Bash path handling, (9) Security model implementation (profiles/permissions/sharing), (10) Flow/Process Builder/Flow Orchestrator automation, (11) Agentforce 2.0 AI agents and autonomous automation, (12) Data Cloud Vector Database with semantic search, (13) Hyperforce public cloud architecture. Provides: comprehensive SFDC object schema knowledge (standard/custom objects, all fields, relationships), complete API reference (REST/SOAP/Bulk/Streaming) for API 63.0/64.0, Apex language mastery with Compression and FormulaEval namespaces (Spring '25 GA), Lightning platform expertise with Winter '26 GraphQL updates and SLDS 2.0 dark mode, SOQL/SOSL optimization, authentication methods (OAuth/JWT/Session), limits and best practices, governor limits handling, integration patterns (ETL/real-time/batch/Data Cloud), metadata API operations, SFDX CLI commands with cross-platform path conversion (MSYS_NO_PATHCONV, shell detection, cygpath), version-specific guidance, platform event architecture, Agentforce 2.0 development with LLM Open Connector, Data Cloud Vector Database for unstructured data and hybrid search, Flow Orchestrator multi-user workflows, Hyperforce cloud-native architecture, and Windows Git Bash/MINGW compatibility for SF CLI deployments. Ensures production-ready, scalable, secure Salesforce solutions following Spring '25/Summer '25 best practices and Well-Architected Framework.
JosiahSiegelComplete Azure-to-Docker migration system for local development with 2025 features. PROACTIVELY activate for: (1) ANY Azure-to-Docker migration task, (2) Azure infrastructure extraction and Docker Compose generation, (3) Azure service emulator setup (Azurite 2025-11-05 API, SQL Server 2025 latest, Cosmos DB vnext Linux, Service Bus official emulator), (4) Local development with Docker Compose Watch mode (hot reload), (5) Database export from Azure SQL/PostgreSQL/MySQL to Docker, (6) Dockerfile generation from Azure App Service configurations, (7) Multi-container orchestration with proper networking and dependencies, (8) Production-ready Docker Compose with health checks and runtime secrets, (9) Azure service mapping (App Service/SQL/Storage/Redis/Cosmos/Service Bus), (10) Development-to-production parity with Azure emulators. Provides: Azure resource extraction and analysis, complete Docker Compose generation with 2025 best practices, Azure emulator configuration (Azurite with latest API, SQL Server 2025 with Vector Search, Cosmos DB vnext Linux-based, official Service Bus emulator), Docker Compose Watch mode for hot reload, database export automation, App Service to Dockerfile conversion, service dependency mapping, network isolation patterns, volume management strategies, environment variable templating, health check implementation, resource limit configuration, security hardening (non-root users, read-only filesystems, capability drops, runtime-only secrets), development override patterns with watch mode, and Azure-to-Docker best practices. Ensures production-ready local development environments that mirror Azure infrastructure with instant hot reload capabilities.
JosiahSiegel