Explore our collection of Agent Skills to enhance your AI workflow.
Manipulates, generates, and extracts data from PDF documents using specialized Python libraries and command-line utilities.
Manages GitHub milestones to organize development issues into time-based delivery phases and track project progress.
Manages Git worktrees for parallel development environments with automated configuration of ports, databases, and environment files.
Streamlines Confluence documentation tasks including page creation, space management, and Atlassian API integration.
Generates comprehensive, generator-ready inline documentation including JSDoc, docstrings, and strategic comments for TypeScript and Python.
Implement advanced LLM prompting techniques like few-shot learning and chain-of-thought to enhance production AI reliability and output quality.
Performs a rigorous 7-point code audit covering security, performance, and maintainability to ensure production-grade software quality.
Implements Clean Architecture, Hexagonal Architecture, and Domain-Driven Design patterns for robust backend systems.
Automates the creation of git worktrees and launches isolated Claude Code agents for parallel feature development.
Manages and resolves git merge conflicts systematically to maintain code integrity during rebases and merges.
Generates and validates executable Python behavior trees for robotic systems using natural language task descriptions.
Breaks complex GitHub issues into granular, manageable sub-tasks with automated linking and documentation.
Builds and orchestrates end-to-end MLOps pipelines from data preparation and model training to production deployment.
Provides comprehensive guidance for building custom tools, plugins, and integrations within the OpenCode ecosystem using TypeScript and Zod-based schema validation.
Enforces Scala 3 coding standards, formatting rules, and architectural patterns to ensure high-quality, testable code.
Architects and implements sophisticated LLM applications using the LangChain framework for agents, memory management, and complex AI workflows.
Automates development lifecycles, CI/CD pipelines, and team release processes to accelerate software delivery and ensure code quality.
Generates robust JSON Schema definitions for precise data validation and API documentation.
Automates the creation of comprehensive GitHub Pull Requests with standardized templates, verification summaries, and proper issue linking.
Repairs tmux socket connection errors and restores communication between clients and the running server without terminating active sessions.
Applies Anthropic's official visual identity, including specific color palettes and typography, to ensure professional and consistent brand styling across various artifacts.
Implements comprehensive testing strategies for JavaScript and TypeScript applications using modern frameworks like Jest and Vitest.
Evaluates the complexity and impact of code changes to determine the appropriate depth for code reviews.
Monitors CI/PR status and implements efficient sleep/wake patterns to optimize orchestration and token usage.
Provides a comprehensive library of domain-specific automation patterns, best practices, and pre-built modules for the n8n workflow platform.
Generates comprehensive mock data, stub functions, and test datasets to isolate code environments and accelerate automated testing.
Applies professional color palettes and font pairings to digital artifacts like slide decks, documents, and landing pages.
Automates the end-to-end development lifecycle for Jira issues using a structured 6-phase orchestration protocol.
Enforces IPv6-centric networking standards across code, configuration, and documentation while treating IPv4 as a legacy fallback.
Integrates React applications with agent runtimes using specialized hooks and context providers for real-time communication and session management.
Scroll for more results...