Claude Code often repeats work or forgets solutions found in past conversations. This skill searches your conversation archive to retrieve past decisions, code patterns, and solutions without consuming your context window.

Code reviews often contain unclear or technically questionable feedback that gets implemented without verification. This skill ensures AI evaluates feedback technically before implementation, preventing bugs and maintaining code quality.

AI assistants often complete implementation tasks but lack structured guidance for integrating work back into the repository. This skill provides a step-by-step workflow for verifying tests, presenting merge and PR options, executing user choices, and safely cleaning up worktrees.

Complex multi-step implementations are challenging to manage safely. This skill breaks development plans into manageable batches with review checkpoints, ensuring quality and catching issues early.

Multiple independent failures waste time when investigated sequentially. This pattern dispatches one AI agent per independent problem domain, letting them work concurrently to solve separate issues in parallel.

Transform vague ideas into concrete implementation plans through structured dialogue. This skill guides you from concept to validated design with incremental validation at each step.

An AI skill for Claude, Codex, and Claude Code

Generating code in monorepos requires navigating complex project structures and selecting the right generator. This skill prioritizes workspace-plugin generators for custom solutions and guides you through running generators with proper verification steps.

Creating skills for AI assistants requires understanding modular design, resource organization, and distribution formats. This guide provides step-by-step instructions for building skills that extend Claude with specialized knowledge and workflows.

Managing feature implementation across scattered todo lists and design documents wastes time and causes missed tasks. Task execution engine reads structured task lists directly from markdown design files and executes them one by one with automatic checkbox updates.

Analyzing screenshots manually to extract features and create task lists is time-consuming and error-prone. This multi-agent skill analyzes UI screenshots in parallel from three perspectives to identify features, interactions, and business logic, then generates a ready-to-use development task checklist.

Feature development often stalls due to unclear requirements and missing context. The Feature Design Assistant guides you through structured information gathering to capture all necessary details before implementation, resulting in complete designs and actionable implementation tasks.

AI agents often plateau in capability after initial training. This skill provides a structured cognitive training loop that helps agents continuously improve reasoning quality, memory use, self-correction, and owner interaction through daily drills and feedback.

Building user interfaces requires finding the right style, colors, and layout patterns. This skill provides a comprehensive database of 50 design styles, 21 color palettes, 50 font pairings, and framework-specific guidelines to create professional interfaces.

Eliminate UI development friction by combining shadcn/ui's accessible component library with Tailwind CSS utility-first styling and canvas-based visual design systems. This skill provides comprehensive reference documentation for 40+ shadcn/ui components, theming and dark mode patterns, accessibility guidelines, responsive design utilities, and Python automation scripts for component installation and Tailwind config generation.

Creating professional designs usually requires hiring a designer or learning complex software. This skill generates logos, brand identity documents, social media images, banners, icons, and presentations directly from your descriptions using AI.

Design systems often break down when tokens are not consistently applied across primitive, semantic, and component layers. This skill generates CSS variables from JSON token definitions, validates token usage in code, and creates brand-compliant slide presentations with Chart.js integration.

This skill provides a structured framework for analyzing codebases. It helps developers quickly understand unfamiliar projects by examining structure, dependencies, and architecture. The analysis covers components, interactions, deployment, and runtime behavior.

Building with serverless databases requires understanding connection methods, scaling behavior, and platform-specific features. This skill provides comprehensive guidance for working with Neon Serverless Postgres across all development scenarios.

Agents need objective criteria to evaluate execution services. This skill provides a deterministic workflow for searching services, inspecting trust evidence, and submitting structured reviews with integer ratings (0-10) to the Agentic Trust catalog.