Explore our collection of Agent Skills to enhance your AI workflow.
Architects type-safe, file-based React navigation systems optimized for performance and Cloudflare Workers deployment.
Orchestrates end-to-end machine learning workflows using industry-standard tools like Airflow, Kubeflow, and MLflow.
Generates production-ready Kubernetes Resource Orchestrator (KRO) definitions using Pulumi TypeScript to automate custom API creation and resource composition.
Automates GitHub repository setup with production-ready CI/CD workflows, security scanning, and standardized issue templates.
Systematizes topic research through complexity-based assessment and automated documentation generation.
Architects and implements high-performance, Git-based CMS solutions using Nuxt Content v3 with SQL storage and MDC syntax.
Performs high-precision, AST-based code searching, linting, and structural refactoring across 20+ programming languages.
Generates valid, production-ready Looplia agentic workflow definitions from skill recommendations and user requirements.
Standardizes shell operations and command orchestration for Claude Code with robust hooks and production-ready automation workflows.
Enforces a strict Test-Driven Development cycle to ensure high-quality, verifiable code implementation.
Generates production-ready Common Expression Language (CEL) for Kubernetes admission control, CRD validation rules, and security policy enforcement.
Provides metacognitive oversight to evaluate plan alignment, focus, and proportionality during development tasks.
Generates high-quality ideas and creative solutions using 30+ research-validated prompt patterns and systematic ideation frameworks.
Architects and develops distributed agent-centric applications using the Holochain framework and Rust toolchain.
Optimizes Claude for building, testing, and maintaining production-grade Python 3.11+ applications and high-performance CLI tools.
Performs in-depth codebase research and documents findings in persistent, structured markdown files.
Optimizes project instructions and CLAUDE.md configurations using Anthropic's official prompt engineering best practices for Claude 4.5.
Generates structured, project-specific rules in a `lifeguard.yaml` file to guide and standardize code reviews.
Simplifies LLM API integration by providing a unified Python interface for over 100 providers using a consistent OpenAI-compatible format.
Manages comprehensive configurations for the Zellij terminal multiplexer, including custom layouts, themes, keybindings, and plugins.
Generates high-quality ElevenLabs text-to-speech audio with expressive controls and Mac-style CLI simplicity.
Generates and validates professional, PyPI-compliant README files in Markdown or reStructuredText to ensure perfect rendering across Python package registries.
Provides a structured process and best practices for creating new Claude skills.
Audits frontend code against industry-standard Web Interface Guidelines to ensure high-quality UX and accessibility compliance.
Enforces mandatory reasoning checkpoints to ensure implementation actions align with verified project reality rather than training data patterns.
Applies semantic line breaks to prose, such as comments and commit messages, to improve readability and maintainability.
Extracts and documents complete design systems from websites, including typography, color palettes, and interactive component patterns.
Applies a Test-Driven Development (TDD) cycle to create and bulletproof other Claude skills, ensuring they withstand pressure and resist rationalization.
Simplifies the installation, configuration, and management of Mozilla Llamafile for running local, OpenAI-compatible LLMs.
Standardizes Git commit messages to enable automated semantic versioning and professional changelog generation.
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