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Found 1,692 Skills
Elite AI/ML Senior Engineer with 20+ years experience. Transforms Claude into a world-class AI researcher and engineer capable of building production-grade ML systems, LLMs, transformers, and computer vision solutions. Use when: (1) Building ML/DL models from scratch or fine-tuning, (2) Designing neural network architectures, (3) Implementing LLMs, transformers, attention mechanisms, (4) Computer vision tasks (object detection, segmentation, GANs), (5) NLP tasks (NER, sentiment, embeddings), (6) MLOps and production deployment, (7) Data preprocessing and feature engineering, (8) Model optimization and debugging, (9) Clean code review for ML projects, (10) Choosing optimal libraries and frameworks. Triggers: "ML", "AI", "deep learning", "neural network", "transformer", "LLM", "computer vision", "NLP", "TensorFlow", "PyTorch", "sklearn", "train model", "fine-tune", "embedding", "CNN", "RNN", "LSTM", "attention", "GPT", "BERT", "diffusion", "GAN", "object detection", "segmentation".
Capture browser console logs and dev server output to files with agent-tail. Use when debugging runtime errors, checking console output, tailing or diagnosing logs, or setting up Vite/Next.js log capture.
ALWAYS use when writing code importing "@vue/test-utils". Consult for debugging, best practices, or modifying @vue/test-utils, vue/test-utils, vue test-utils, vue test utils, test-utils, test utils.
ALWAYS use when writing code importing "@formkit/core". Consult for debugging, best practices, or modifying @formkit/core, formkit/core, formkit core, formkit.
Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging norm stats and GPU memory issues.
Use when the user asks about the Alpic CLI (`alpic`) — deploying MCP servers, viewing logs, debugging deployments, managing environment variables, configuring the playground, connecting git, and publishing to the MCP Registry.
Designs, reviews, and debugs DynamoDB data layers from design axioms — enumerates access patterns, chooses partition/sort keys and GSIs, decides single-table vs. multi-table, configures Streams, Global Tables, TTL, and zero-ETL integrations to OpenSearch/Redshift/SageMaker Lakehouse, and produces a defensible data-layer design with a monthly cost estimate and optional live validation. Applies whenever a user is designing, reviewing, or refactoring anything backed by DynamoDB — schemas, access patterns, GSIs, single- vs. multi-table choices, Streams consumers, transactional outboxes, Global Tables, zero-ETL pipelines — even when they don't say "axioms" or "design review." Also applies when debugging hot partitions, throttling, unbounded Scans, LWW conflicts, or surprise bills on DynamoDB workloads.
Master Go concurrency with goroutines, channels, sync primitives, and context. Use when building concurrent Go applications, implementing worker pools, or debugging race conditions.
Use when building distributed apps with Aspire; orchestrating .NET, JavaScript, Python, or polyglot services; when environment variables or service discovery aren't working; when migrating from .NET Aspire 9 to 13+ or Community Toolkit; when seeing AddNpmApp deprecated errors; when OTEL not appearing in dashboard; when ports change on restart breaking OAuth; when configuring MCP server for AI assistants; when debugging Aspire apps and need to check resource status or logs
Receive and verify GitHub webhooks. Use when setting up GitHub webhook handlers, debugging signature verification, or handling repository events like push, pull_request, issues, or release.
Use when implementing BGTaskScheduler, debugging background tasks that never run, understanding why tasks terminate early, or testing background execution - systematic task lifecycle management with proper registration, expiration handling, and Swift 6 cancellation patterns
Playwright browser automation API, web scraping, and tooling. Covers locator strategies, assertions, API testing, stealth mode, anti-bot bypass, authenticated sessions, screenshots/PDFs, Docker deployment, configuration, debugging, and MCP integration with AI agents. Prevents documented errors including CI timeout hangs, extension testing failures, and navigation issues. Use when automating browsers, scraping protected sites, bypassing bot detection, generating screenshots/PDFs, configuring Playwright Test, troubleshooting Playwright errors, or learning Playwright API patterns. For E2E test architecture, Page Object Models, CI sharding strategies, or test organization patterns, use the e2e-testing skill instead.