Skill UI

This skill provides a comprehensive, structured workflow for managing projects, issues, and team workflows within the Linear platform. It supports natural-language project management, allowing users to perform tasks like sprint planning, bug triage, and workload balancing by interacting with the Linear MCP server and various specialized tools.

This meta-skill is designed for complex decision analysis when a user provides or references structured documents such as contracts, quotes, spreadsheets, or notices. Instead of simple summarization, it extracts key evidence, identifies risks (e.g., renewal risk, payment terms), and structures the output into decision-ready formats, such as 'sign/reject/negotiate' recommendations, evidence tables, or required next actions. It supports input from PDF, DOCX, and XLSX formats.

Designed for complex troubleshooting in home or small-team environments. This meta-skill orchestrates the entire process, guiding users through symptom intake, environment capture, external knowledge lookup, and generating a safe, step-by-step, and reversible repair plan for issues involving networks, Docker, Git, printers, and more.

A powerful skill for generating high-quality single images from text prompts (Text-to-Image) or modifying existing images (Image-to-Image). It utilizes OpenRouter, supporting various aspect ratios and resolutions, making it ideal for concept art, product rendering, or any single visual asset creation. The tool handles sophisticated parameters like model choice and failure fallbacks.

This tool facilitates comprehensive research by pulling relevant information from multiple Notion sources. It synthesizes scattered data into highly structured documentation, such as detailed briefs, comparative analyses, or executive reports. It ensures all claims are supported by accurate inline citations and links, making it ideal for market research, project documentation, or academic reporting where source traceability is critical.

This tool assists researchers in structuring academic papers by mapping specific claims across different sections (Introduction, Method, Results, Discussion) to required external citations (BibTeX keys). It enforces citation density rules and ensures the correct role alignment (e.g., background, comparison, limitation) before the actual drafting process, guaranteeing that every core claim is properly supported and distributed.

This meta-skill orchestrates the entire academic writing workflow, from initial requirement extraction (topic, length, audience) to drafting, citation management, and final LaTeX/PDF compilation. It supports various modes, including compact skeletons for quick drafts and full manuscripts for publication-ready work. Ideal for users needing structured help with research papers or academic manuscripts.

This specialized tool is designed to curate and structure academic source material for long-form research papers. It takes paper topics, user preferences, search results, and bibliography entries as input. The output is a highly structured source pack, clearly identifying primary, supporting, and excluded sources, along with coverage notes to ensure research depth and methodological rigor.

Generates high-quality, short video clips (3-15s) using the Seedance 2.0 model. This tool accepts structured English prompts, an optional first-frame image, and an optional identity/style reference image for continuity. It supports dual backends (OpenRouter, Volcengine, BytePlus) to maximize accessibility and reliability for cinematic shot generation.

A utility for managing and installing specialized AI skills into the Codex environment. It supports fetching curated skills from predefined sources (like openai/skills) or installing custom capabilities directly from any GitHub repository, including private ones. It handles listing available skills, installing specific modules, and provides robust fallback methods (download/git sparse checkout).

Designed to capture a fully functional, standalone static HTML file from any modern web application (React, Next.js, Vue, etc.). It resolves all computed styles and inlines CSS and images (as Base64) into the output, ensuring the captured view can be shared or archived without external dependencies. Supports both automated snapshotting via Puppeteer and interactive capture.

This utility burns an SRT subtitle track directly into an MP4 video file using ffmpeg's libass filter. It re-encodes the video (H.264) while copying the audio untouched. It supports defining custom font fallback chains (e.g., CJK fonts) and provides detailed control over font size, margins, and video encoding parameters (CRF, preset) for professional subtitling workflows.