AIエージェントの能力を拡張するClaudeスキルの完全なコレクションをご覧ください。
Accelerates full-stack React development using TanStack Start for server functions, file-based routing, and Cloudflare Workers deployment.
Streamlines the creation of new WebAssembly frontend pages and routing within the Lightfriend Yew framework.
Orchestrates multi-agent evaluations of newly created Claude Code skills to determine optimal auto-trigger configurations based on safety, frequency, and token efficiency.
Streamlines iOS development workflows by configuring Model Context Protocol (MCP) session defaults for Xcode projects and simulators.
Implements high-performance mobile animations using Reanimated 3 and Gesture Handler to create fluid, 60fps user experiences.
Optimizes AgentDB vector databases through quantization, HNSW indexing, and advanced caching to maximize search speed and minimize memory overhead.
Deploys applications to Coolify using best practices to ensure zero-downtime releases and production stability.
Deploys applications to Coolify using systematic best practices and verification checklists to ensure zero-downtime production stability.
Automates and manages high-reliability deployments to Coolify while enforcing industry best practices for production stability.
Orchestrates multi-agent swarms for distributed research, full-stack development, and automated testing using the Claude Flow framework.
Transforms vague user inputs into structured, high-performance prompts using the TCRO framework and phase-specific clarification.
Removes AI-generated verbosity, conversational fillers, and redundant comments to improve information density and clarity.
Removes AI-generated verbosity, conversational filler, and redundant code comments to improve information density.
Performs differential topologically associating domain (TAD) analysis to identify significant chromatin architecture changes between experimental conditions using HiCExplorer.
Boosts AI response quality by 45-115% using research-backed incentive framing and expert persona techniques.
Automates repetitive development tasks through a continuous iteration loop with objective completion criteria and safety caps.
Orchestrates complex AI agent swarms and event-driven workflows using the Flow Nexus cloud platform.
Retrieves comprehensive GitHub user and organization profile data including repository counts, follower statistics, and account metadata.
Captures and retrieves hard-won coding patterns and architectural lessons in a persistent vector database.
Automates cross-repository synchronization, dependency alignment, and architectural standardization using AI swarm orchestration.
Transforms vague user inputs into highly structured, high-performance specifications using the TCRO framework and phase-specific clarification.
Performs genome-wide DNA methylation analysis to characterize patterns, genomic feature distributions, and sample similarities from sequencing data.
Automates the entire GitHub release lifecycle using AI swarms for intelligent versioning, multi-platform deployment, and rollback orchestration.
Ensures codebase reliability through automated truth scoring, quality verification, and instant git-based rollback systems.
Provides comprehensive guidelines and best practices for conducting high-quality code reviews and writing constructive feedback.
Analyzes developer prompts to automatically suggest optimized Rails workflows and route tasks to specialized utility agents.
Performs A/B compartment shift analysis between Hi-C samples using PC1 eigenvector values and replicate-aware statistical methods.
Orchestrates multi-phase research across codebases and documentation to provide evidence-backed insights and architectural synthesis.
Transforms ambiguous user input into high-precision, structured TCRO prompts to maximize AI output quality and consistency.
Enhances AI response quality by 45-115% through research-backed techniques like expert personas and stakes-based framing.
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