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。
Configures and manages life-cycle hooks to enable autonomous task continuation and security validation within Claude Code.
Generates and maintains comprehensive technical documentation including API specs, READMEs, and architecture diagrams.
Exports Claude Code and Cursor conversation transcripts directly to a structured Notion database for documentation and archival.
Performs comprehensive system audits and diagnostic health checks for Maestro skills, agents, hooks, and memory systems.
Manages and optimizes Claude Code session context by automatically summarizing history and discarding redundant data to stay within token limits.
Analyzes existing codebases to generate continuity ledgers and accelerate project familiarity for Claude.
Performs differential gene expression analysis for bulk RNA-seq data using Python-based DESeq2 workflows.
Automates the continuous improvement and validation of Ralph Wiggum prompt skills through iterative self-review cycles.
Implements a 5-layer verification pyramid to ensure production-grade code quality through automated checks and LLM-as-judge evaluation.
Starts a fresh project session by loading core context files and initializing a structured session log.
Conducts professional, senior-level frontend code reviews directly on GitHub Pull Requests using the GitHub CLI and local scripts.
Deploys production-grade Amazon EKS clusters using Terraform best practices and official implementation modules.
Performs real-time sentiment analysis on Twitter/X content using Grok's native integration and natural language processing.
Executes an intensive code quality suite combining ESLint, TypeScript compilation, and unused code detection to maintain high development standards.
Analyzes Claude Flow swarms to detect performance bottlenecks, profile operations, and provide actionable AI-powered optimization recommendations.
Extracts actionable patterns and learnings from autonomous coding sessions to optimize future AI performance.
Deploys and manages comprehensive Grafana dashboards for monitoring Claude Code performance, costs, and session health.
Verifies technical requirements and gathers real-time information through structured web searches and documentation analysis.
Manages end-to-end Railway.com deployment workflows including source deployment, monitoring, health verification, and rollback strategies.
Manages seamless transitions between AI agents and sessions by serializing state and bridging context for continuous workflows.
Guides users through workspace capabilities, specialized agents, and multi-agent workflows using interactive discovery.
Analyzes Java codebase architecture to identify structural weaknesses and generate incremental refactoring plans.
Conducts systematic technical research across web sources, MCP servers, and GitHub repositories to identify best practices and implementation patterns.
Automates the creation of custom, high-performance Claude skills when existing tools cannot address complex or novel tasks.
Generates and customizes professional-grade static, animated, and interactive visualizations using Python's foundational plotting library.
Accesses and analyzes Railway build, deployment, and runtime logs for debugging and monitoring applications.
Builds machine learning models and embeddings for genomic interval data to enable similarity searches, clustering, and single-cell analysis.
Streamlines the development, deployment, and management of serverless bioinformatics workflows on the LatchBio platform.
Streamlines the deployment of Dr. Sophia AI to Railway with environment-aware build systems and automated workflows.
Validates Claude Code skill functionality and usability through comprehensive scenario-based testing operations.
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