Skill UI

This skill processes raw weekly CRM export files (CSV) to generate a clean, structured regional sales summary. It automatically removes duplicate records, calculates the total revenue for each defined region, and outputs the results as a standardized JSON object. Ideal for automating reporting pipelines or preparing data for dashboards.

Converts complex, long-form markdown (like RFCs, specs, or reports) into a single, polished, and lightly interactive HTML file. It features a sticky Table of Contents, search functionality, advanced code-copy buttons, and integrates with design systems for professional branding, all without needing a build step or framework runtime.

This skill converts a structured markdown file containing multiple slides into a single, self-contained, interactive HTML presentation. It supports advanced presentation features such as Presenter Mode (with speaker notes, clock, and next slide preview), URL-hash deep linking, and print-to-PDF functionality. Ideal for creating professional, browser-based slide decks directly from simple markdown source.

A comprehensive tool for extracting YouTube transcripts, searching videos, browsing channels, and monitoring new uploads. It supports detailed transcript analysis, content summarization, and playlist management by leveraging the TranscriptAPI. Ideal for researchers, content strategists, and market analysts who need structured data from video content without downloading files.

This skill generates high-fidelity, print-ready academic conference posters (e.g., for ICML, NeurIPS, CVPR) as a single HTML/CSS file, rendered to PDF via headless Chromium. It enforces rigorous, measurement-driven design gates, incorporates real paper figures with provenance, and adheres to strict academic guidelines (like two-hue systems) to ensure professional, publication-quality results. Ideal for researchers needing to design or refine conference posters.

This skill helps developers build, validate, and troubleshoot deep links for major coding environments like VS Code, Cursor, and Codex. It is essential when creating clickable, actionable links (especially in chat platforms like Slack) that direct users to specific files, threads, or settings within an application.

This tool provides an end-to-end workflow for managing massive codebase migrations, framework upgrades, and structural refactors across hundreds of files. It uses a specialized CLI to orchestrate issue tracking, create reviewable PR batches, and verify CI status, ensuring complex changes are implemented safely and incrementally.

This skill provides a direct, fast shell invocation to capture the current git diff (staged, working-tree, or specific file list) as raw text. It is designed to replace slower LLM agent steps that merely execute 'git diff' commands, significantly speeding up CI/CD workflows and meta-steps that require repository state analysis.

This meta-skill provides a complete pipeline to bootstrap a domain knowledge base from any single seed input (URL, PDF, Git repository, or free text). It automatically classifies the source type, ingests the content using a multi-search engine, persists the summary to memory, and finally generates a structured XLSX index file, making the information immediately searchable and usable.

This meta-skill takes a single source text and automatically renders it into four professional, distinct deliverables: a detailed Word report (.docx), a presentation slide deck (.pptx), a structured Excel data file (.xlsx), and a clean PDF version (.pdf). It ensures consistency across all required formats and greatly enhances content deployment efficiency for different business audiences.

This meta-skill orchestrates a comprehensive workflow for analyzing PDF documents. It handles complex tasks such as summarizing, cross-document comparison, and targeted Q&A. It ensures findings are traceable by indexing evidence from various sources (full PDFs, pasted excerpts, etc.) and synthesizing structured insights across multiple files.

This utility serves as a stub experiment generator, primarily for demonstration purposes within meta-paper writing workflows. Given a specific topic phrase, it deterministically produces a consistent CSV file containing simulated experimental results. This function allows users to prototype and test complex paper structures and formats without needing access to real scientific data.