Explore our collection of Agent Skills to enhance your AI workflow.
Automates the code review process by dispatching AI subagents to verify feature implementation and catch issues before merging.
Manipulates, extracts, and generates PDF documents programmatically using Python libraries and command-line utilities.
Provides standardized, proven development patterns and architectural guides for building and optimizing AI-assisted workflows.
Implements robust multi-tenant data isolation in Ruby on Rails applications using an Account-based boundary.
Generates publication-quality, journal-ready figures and multi-panel scientific visualizations following academic standards.
Reviews technical documentation for factual accuracy, validates code examples, and identifies broken links.
Integrates Google's Gemini-3-pro-preview model into Claude Code for multimodal analysis, massive context processing, and real-time grounding.
Ensures Python compatibility shims correctly export private functions during module reorganizations.
Automates the generation of standardized pull request descriptions and conventional commit titles by analyzing git changes.
Automates the recording of actual trading results against predicted signals to enable accurate performance metrics and model retraining.
Generates professional PDF reports featuring formatted text, data tables, and embedded visualizations using the reportlab Python library.
Streamlines software development workflows with seven specialized agents for code review, debugging, testing, and git operations.
Generates granular, TDD-focused implementation plans to guide complex software development tasks with precision.
Simplifies complex programming concepts using visual ASCII diagrams and relatable real-world analogies.
Eliminates HOLD bias in reinforcement learning trading models by calibrating reward functions and slippage penalties.
Analyzes codebases to calculate service costs, model usage patterns, and implement optimized pricing strategies and payment systems.
Facilitates complex decision-making through a multi-agent debate simulation that analyzes problems from diverse cognitive perspectives.
Transforms vague project ideas into concrete technical specifications through structured collaborative dialogue and architectural analysis.
Builds secure, production-ready desktop applications using Electron 33, Vite, React, and TypeScript with type-safe IPC and native module support.
Optimizes Apache Spark jobs through advanced partitioning, memory management, and shuffle performance tuning.
Generates valid Mission Control ScrapeConfig YAML from natural language for various infrastructure and cloud sources.
Facilitates first-principles reasoning and deep conceptual analysis to solve complex architectural and coding challenges.
Standardizes project-level plugin configuration and state management using YAML frontmatter and Markdown files.
Standardizes Playwright end-to-end test development by enforcing high-performance locators, web-first assertions, and reliable async patterns.
Enables interactive, multi-pane terminal user interfaces for Claude to manage calendars, documents, and complex data visualizations.
Simplifies Vercel deployments, environment variable management, and domain configuration directly through Claude Code.
Processes video files through audio extraction, format conversion, and automated AI transcription using Whisper and FFmpeg.
Reloads hierarchical and rolling project memory from local documentation files into the current Claude session.
Optimizes Python dataclasses for memory efficiency, immutability, and validation using advanced PEP 557 patterns.
Optimizes cloud infrastructure spending across AWS, Azure, and GCP through resource rightsizing, tagging strategies, and reserved capacity planning.
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