Skill UI

A comprehensive guide to configuring and maximizing the potential of Claude Code, an advanced agentic coding tool. This resource details best practices, setup templates (CLAUDE.md), advanced prompting techniques (e.g., thinking keywords), and debugging strategies for building reliable, complex software autonomously.

This bundle provides a comprehensive framework for diagnosing and fixing common issues when AI code generation is incorrect within Cursor. It systematically covers the root causes of poor suggestions, including context mismanagement (missing, wrong, or overflowing context), model hallucinations, and ambiguous prompting. Use this guide to improve the accuracy and reliability of AI-assisted coding workflows.

Utilize the Kling AI API to generate high-quality, cinematic videos directly from descriptive text prompts. This advanced tool supports professional modes, camera movement control (pan, tilt, zoom), negative prompting, and synchronized native audio, making it ideal for professionals building robust text-to-video pipelines and creative content generation.

Guides how to craft detailed prompts for Google Stitch so it generates high-quality web and mobile UI designs, covering specificity, visual style, multi-screen structure, platform targeting, and iterative refinement.

This workflow suite provides robust tools for automating complex, multi-step software development tasks. It allows users to define reusable workflows (like feature scaffolding, deployment pipelines, and quality checks) that are triggered via slash commands. By integrating persistent 'Memories', it maintains project context across sessions, significantly reducing repetitive prompting and standardizing development practices.

Manage cron-based schedules by querying current jobs, prompting user decisions, and creating or deleting tasks with self-contained messages so automated operations run exactly when needed.

This coach guides users through a progressive mastery of AI, structured across three layers: AI User (prompting), AI-Enhanced Worker (workflow integration), and AI Builder (ML foundations). It uses Socratic questioning, layered scaffolding, and spaced repetition to build genuine, transferable AI literacy, moving beyond simple copy-pasting prompts to deep conceptual understanding of models, transformers, and RAG.

This skill acts as an expert Design Systems Lead, analyzing complex technical assets (HTML, CSS, screenshots) from existing projects. It synthesizes a comprehensive 'Semantic Design System' into a structured DESIGN.md file. This output serves as the authoritative 'source of truth' for AI prompting, ensuring that any new UI generated by tools like Stitch adheres perfectly to the established visual language, color palette, and component standards.

An advanced AI tool utilizing Meta's Segment Anything 2 (SAM2) model for interactive, pixel-perfect object segmentation. Users can click on any object within a frame or video to automatically generate precise masks. Key features include point/box prompting, video tracking across multiple frames, and seamless integration into Annotation Studio workflows, making it ideal for large-scale data labeling and video analysis pipelines.

This skill provides access to the Anthropic Claude Managed Agent runtime, which is a cloud-native, persistent environment for running complex, long-running, or asynchronous AI tasks. Unlike local WASM agents, the managed runtime provides a full container, persistent filesystem, and robust state management across multiple turns. It supports the entire agent lifecycle: creation, prompting, status inspection, event logging, and mandatory termination.

This skill manages repeated rollouts and recursive prompting by maintaining an append-only decision ledger. It tracks trials, marks, and coherence checks to prevent auto-approval of live trading or destructive actions. Ideal for high-dimensional search, stochastic optimization, and ensemble comparison requiring visible evidence trails.

Restructures any vague build, research, or legal-drafting request into a highly structured IRAC (Issue, Rule, Analysis, Conclusion) prompt. This method optimizes output quality for frontier models by forcing the definition of constraints, underlying rules, required reasoning, and precise deliverables, moving beyond simple prompting.