Explore our collection of Agent Skills to enhance your AI workflow.
Audits and secures web applications against the most critical security vulnerabilities identified by OWASP.
Automates the creation of high-quality AI avatar videos and talking head content using the HeyGen API.
Implements real-time voice agents, high-accuracy transcription, and text-to-speech using leading audio AI providers.
Builds production-ready, real-time dashboard interfaces using responsive React layouts and advanced data table components.
Implements sophisticated Python testing workflows using custom markers, parallel execution with xdist, and advanced fixture architecture.
Optimizes LLM performance through production-ready patterns including Chain-of-Thought, dynamic few-shot learning, and automated prompt tuning.
Implements autonomous reasoning patterns like ReAct and Plan-and-Execute to enable LLMs to solve complex, multi-step tasks.
Analyzes and resolves application bottlenecks across the full stack, from database queries to frontend bundle sizes and Core Web Vitals.
Models complex business logic using tactical DDD patterns including entities, value objects, and bounded contexts.
Configures and optimizes your OrchestKit environment with an interactive setup for skills, agents, and advanced Claude Code settings.
Optimizes web image performance and user experience using Next.js 16 patterns, modern formats like AVIF/WebP, and responsive loading strategies.
Detects and alerts on non-error LLM agent failures including tool skipping, infinite loops, and degraded output quality.
Implements advanced Self-RAG and Corrective-RAG architectures for self-correcting AI retrieval systems.
Mocks network-level API requests for frontend testing using Mock Service Worker 2.x standards.
Streamlines the creation of high-quality, accessible design systems using Radix UI unstyled primitives.
Streamlines the creation and management of test data using factories, fixtures, and automated database seeding patterns.
Monitors LLM application quality and input distribution shifts to detect performance degradation in production environments.
Automates the creation and management of AI-powered talking head videos via the HeyGen API.
Implements production-ready real-time data streaming patterns using SSE, WebSockets, and ReadableStream for high-performance applications.
Detects and alerts on hidden LLM agent failures such as tool skipping, infinite loops, and degraded output quality.
Provides structured frameworks for market sizing, competitive intelligence, and industry dynamics assessment.
Coordinates complex multi-agent workflows using a centralized supervisor-worker orchestration pattern.
Optimizes application speed and resource usage across the full stack through profiling, database tuning, and frontend analysis.
Validates and sanitizes untrusted user input using industry-standard Zod and Pydantic patterns to prevent security vulnerabilities.
Implements deterministic testing patterns and quality metrics for LLM-based applications using DeepEval and RAGAS.
Employs systematic debugging methodologies like the 5 Whys and Fishbone diagrams to identify the underlying sources of software failures and incidents.
Mocks network-level API requests using MSW 2.x to create deterministic and resilient frontend tests.
Implements complex background task patterns, enterprise workflows, and production-grade monitoring for Celery in Python environments.
Implements sophisticated Celery task patterns including complex workflows, priority queuing, and enterprise-grade monitoring.
Enforces strict layer separation and Clean Architecture patterns in FastAPI projects through automated, blocking validation.
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