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Found 528 Skills
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastructure.
Write unit and integration tests for Angular v21+ applications using Vitest or Jasmine with TestBed, component harnesses, and modern testing patterns. Use for testing components with signals, OnPush change detection, services with inject(), and HTTP interactions. Triggers on test creation, testing signal-based components, mocking dependencies, or setting up test infrastructure.
OSS-Fuzz provides free continuous fuzzing for open source projects. Use when setting up continuous fuzzing infrastructure or enrolling projects.
Use when writing E2E tests with Playwright, setting up test infrastructure, or debugging flaky browser tests. Invoke for browser automation, E2E tests, Page Object Model, test flakiness, visual testing.
Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. Use when: voice ai, voice agent, speech to text, text to speech, realtime voice.
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
Upstash QStash expert for serverless message queues, scheduled jobs, and reliable HTTP-based task delivery without managing infrastructure. Use when: qstash, upstash queue, serverless cron, scheduled http, message queue serverless.
Implements infrastructure as code using Terraform, Kubernetes, and cloud platforms. Designs scalable architectures, CI/CD pipelines, and observability solutions. Provides security-first DevOps practices and site reliability engineering guidance.
A/B testing and content experimentation methodology for data-driven content optimization. Use when implementing experiments, analyzing results, or building experimentation infrastructure.
Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.
Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to set up AGENTS.md, add intent layer, make agents understand the codebase, or scaffolding AI-friendly project documentation.
Help users build and scale internal platforms and technical infrastructure. Use when someone is deciding whether to build vs buy tooling, designing developer platforms, creating shared services, or managing technical debt at scale.