Explora nuestra colección completa de Habilidades de Claude que extienden las capacidades de los agentes de IA.
Manages the automated curation and multi-agent validation of high-quality datasets for LLM evaluation.
Implement and compare multi-agent orchestration frameworks like CrewAI, OpenAI Agents SDK, and Microsoft Agent Framework for specialized AI workflows.
Implements robust Retrieval-Augmented Generation (RAG) patterns to ground LLM responses with accurate, cited, and validated external data.
Implements high-performance, isolated unit testing patterns using the AAA methodology across TypeScript and Python environments.
Calibrates and positions precise video annotations, arrows, and callouts within Remotion compositions using interactive debug grids.
Documents significant architectural decisions using standardized Nygard templates to preserve technical context and trade-offs.
Compiles high-quality, programmatically generated demo videos and animations using the Remotion framework.
Manages the multi-agent curation of high-quality training and testing datasets with automated quality scoring and bias detection.
Coordinates multiple parallel Claude Code instances across Git worktrees to prevent file conflicts and synchronize architectural decisions.
Optimizes multi-directory context and specialized instructions for complex monorepo structures within Claude Code.
Automates GitHub release workflows using semantic versioning, automated changelog generation, and GitHub CLI integration.
Optimizes Claude Code sessions by condensing conversation history using structured, anchored summarization to prevent token limit degradation.
Implements robust, scalable design systems with standardized tokens, atomic component architecture, and full accessibility compliance.
Automates GitHub release workflows using semantic versioning and changelog generation via the gh CLI.
Integrates ElevenLabs text-to-speech capabilities into video production pipelines for automated narration, voice selection, and synchronized timing.
Enhances search precision in RAG pipelines by re-scoring retrieved documents using high-accuracy Cross-Encoders and LLM relevance patterns.
Implements RFC 9457 Problem Details to provide standardized, machine-readable HTTP API error responses for modern backend services.
Designs and optimizes SQL and NoSQL database schemas with professional-grade normalization, indexing, and migration patterns.
Implements SOLID principles, hexagonal architecture, and Domain-Driven Design (DDD) patterns for building maintainable and testable backends.
Optimizes video thumbnails and first-frame visibility to maximize click-through rates and viewer retention across digital platforms.
Generates professional, animated technical visualizations to showcase agent workflows, spawning logic, and system architectures using the Manim engine.
Builds type-safe, production-ready GraphQL APIs using the Strawberry library and FastAPI integration.
Simplifies Large Language Model fine-tuning and alignment using parameter-efficient techniques like LoRA, QLoRA, and DPO.
Implements high-performance data fetching, caching, and optimistic UI updates using TanStack Query v5 best practices.
Optimizes Large Language Model inference for production environments using vLLM, advanced quantization, and speculative decoding techniques.
Implements a robust 8-layer security architecture to harden AI pipelines and protect LLM integrations from end-to-end vulnerabilities.
Generates high-conversion opening lines and attention-grabbing intros for video content using 12 proven copywriting patterns.
Automates end-to-end browser testing using Playwright 1.58+ with AI-assisted test generation and self-healing capabilities.
Implements automated quality gates, LLM-as-judge patterns, and RAGAS metrics to ensure reliable and grounded AI outputs.
Implements comprehensive observability frameworks for structured logging, Prometheus metrics, distributed tracing, and system alerting.
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