Skill UI

The Research Literature Review tool is designed to search, analyze, and summarize information from diverse academic sources. It integrates local PDF libraries, Zotero collections, Obsidian notes, and multiple web APIs (Semantic Scholar, DeepXiv, etc.). Use it when you need to conduct a comprehensive literature review, find related academic work, or understand the core ideas of a specific research paper.

An autonomous factory for generating production-ready, cross-platform AI agent skills. It accepts raw, unstructured human input—such as transcripts, PDFs, screenshots, vague ideas, or code snippets—and reverse-engineers the complete workflow logic. It bridges the gap between human intent and functional agent specifications, allowing users to automate complex processes without writing code.

Validate business ideas with Sahil Lavingia’s Minimalist Entrepreneur playbook by selling a manual version, defining precise users, testing processes without code, and gauging if customers will pay before building.

This skill helps refine vague, raw ideas into sharp, actionable concepts. It guides users through structured divergent thinking (expanding options, generating variations) and convergent thinking (stress-testing assumptions, clustering directions). The process culminates in a detailed one-pager including Problem Statements, MVP Scope, and key assumptions to validate, ensuring focus and clarity before development.

This system treats ideas like living species on an 'evolution island.' Instead of simple storage, it runs structured, multi-round iterations simulating biological processes: competition, crossbreeding, and mutation. Users input initial concepts, and the tool systematically evaluates them using a 6-dimensional scoring framework (Novelty, Feasibility, Value, etc.). It helps users deepen viability, discover unexpected connections between disparate ideas, and prioritize the most robust concepts for development and investment.

A persistent, structured knowledge base designed to accumulate and connect all research artifacts—including papers, ideas, experiments, and claims—across the entire research lifecycle. Inspired by LLM Wiki patterns, it builds a comprehensive, evolving graph of knowledge by tracking typed relationships (e.g., supports, contradicts, extends), ensuring that findings are compounded and never re-derived. Ideal for complex, multi-stage scientific projects.

A comprehensive skill designed to convert vague ideas, initial concepts, or high-level requirements into structured, detailed, and approved technical specifications. It enforces a rigorous, multi-step workflow, guiding users through context exploration, proposing multiple architectural trade-offs, and iteratively refining the design until a complete specification document is ready for the implementation phase.

Transform raw ideas, articles, or technical material into polished, engagement-optimized LinkedIn posts. This skill leverages Unicode typography (bold, italic) to simulate rich formatting that respects LinkedIn's plain text limitations. It utilizes proven structural patterns (Hook → Content → CTA, Listicle, Story) and best practices for professional social media marketing, helping users create high-impact, scannable thought leadership content.

This coach is designed to systematically develop creative thinking and problem-solving skills. It guides users through established methodologies such as Design Thinking, SCAMPER, TRIZ, and Lateral Thinking. It teaches users how to move beyond initial ideas, overcome creative blocks, and apply structured frameworks to generate, refine, and implement novel solutions across various domains. Ideal for students, professionals, and entrepreneurs facing complex challenges.

This expert acts as a Design Systems Lead and Prompt Engineer for creating high-fidelity, consistent UI designs. It transforms vague ideas into structured specifications by enhancing prompts with professional UI/UX terminology, synthesizing design system source files, and managing multi-step generation and editing workflows using the Stitch MCP.

This skill acts as a specialized prompt engineer for AI design tools. It transforms vague, rough UI/UX ideas into polished, highly optimized prompts. It systematically enhances prompts by injecting missing details such as specific components, design system adherence (colors, typography), page structure, and platform context, ensuring the resulting command is professional and ready for superior AI generation.

This skill acts as an intensive sparring partner, rigorously questioning any provided plan, design, or concept. It guides the user through every decision branch, resolving dependencies one by one until a comprehensive and shared understanding is achieved. Ideal for stress-testing ideas, identifying blind spots, and ensuring the robustness of complex projects before implementation.