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Lets Claude Code watch videos: extracts frames with ffmpeg and transcribes timestamped audio from local files or YouTube links, to review footage, summarize lectures or find on-screen text. Needs Node.js 20+ and ffmpeg (yt-dlp for YouTube); transcribe with local Whisper or a Gemini/OpenAI key.

Stem separation CLI built on UVR models: splits audio into vocals and accompaniment in one command, isolates drums, bass and other stems, or removes noise and reverb; handy for stripping background music or extracting clean vocals. Models download on first use; needs Python and FFmpeg.

Manages a Microsoft 365 tenant with one m365 command: SharePoint, Teams, OneDrive, Outlook, Planner, Power Platform and more, with JSON output and JMESPath filtering. An open-source PnP community project, not officially supported by Microsoft; register an Entra app before signing in.

Two-stage paper skills: planning studies the style of your target preprint server (e.g. PhilArchive, arXiv), finds gaps in the literature and scores a seven-dimension mock review; writing drafts and checks each chapter from the outline. Suits philosophy and interdisciplinary work; needs Python 3.

Self-hosted engine that maps lab results, checkup reports and wearable data to standard metrics so agents can chart trends, citing the source file for every number. uvx mirobody mcp gives the coding tools; full records need Docker and an LLM API key. A doctor should review results.

Turns a paper (arXiv link or PDF) into method diagrams, slides with a generated image per page (PPTX/PDF export) and an in-depth HTML explainer with formulas, for lab meetings and lectures. No API key; images use Codex's built-in generator or, in Claude Code, a separate image skill.

Adds voice conversations to Claude Code and other agents: speak, and it detects silence, transcribes, and reads replies aloud. Runs offline with local Whisper and Kokoro, or uses OpenAI's speech APIs; needs a microphone and speakers.

Opens HTML, Markdown or localhost pages in the browser via npx human-review so you can edit text directly and leave anchored comments, then sends every edit and comment back to the agent in one batch to apply to the source.

Submission skill packs tailored to 700+ journals and conferences, from AER, Nature and NEJM to top CS venues and leading Chinese journals, to revise papers to each venue's scope, style and requirements. Add its Claude Code marketplace per the README, then install packs per journal.

Two companion skills: /tutor-setup turns PDFs, lecture notes or a codebase into an Obsidian study vault with concept notes and practice questions, and /tutor quizzes you with multiple-choice questions on weak spots and tracks mastery. For students reviewing or self-studying; best viewed in Obsidian.

Turns books, PDFs, slides, Word files and web pages into a traceable knowledge base and an offline interactive study page with core frameworks, a glossary, a concept map, self-tests and local notes, keeping source text apart from model additions. Needs Python 3.10+.

Generates book covers, movie posters, article covers and social images from one sentence, picking colors and composition from 30+ poster masters' styles to suit the subject. Rendering directly needs Python and a PipeLLM image API key; or just generate prompts for another image tool.

Local transcription that's compatible with the OpenAI Whisper CLI but faster and lighter: outputs SRT/VTT subtitles or text and can transcribe a live microphone. Needs Python; models download on first run; speaker labels need pyannote.audio and a Hugging Face token.

Jupyter's official tool for notebook assignments: once teachers mark up questions and solutions, the CLI generates student versions, collects submissions, auto-grades and produces feedback. Suits programming and data courses. Needs Python and Jupyter; assignments must use nbgrader's markup.

Local LLM-powered document translator for PDF, Word, Excel, EPUB, SRT subtitles and more; Word and Excel keep their formatting, glossaries can be built automatically, and agents can submit jobs via MCP. Needs uv and an OpenAI-compatible API key; translated PDFs lose the original layout.

X's (formerly Twitter) official API command-line tool. Once authorized, agents can post for you, upload images and video, and query post and account data; it can also run as an MCP server for Claude. Needs an X developer account and app; the X API is pay-per-use, so buy credits first.

Web search and page reading for agents through a self-hosted or trusted SearXNG metasearch instance, with no paid search API key. Requires a SearXNG instance with JSON output enabled.

Pulls new papers from Hugging Face Daily Papers and arXiv, scores them by research area into a recommendation page, and writes deep-read Obsidian notes for key ones; can also batch-read Zotero collections. Needs Python 3, Obsidian and poppler; copy the whole skills folder per the README.

Turns a paper (title, DOI, arXiv ID or local PDF) into a structured Obsidian note covering the research question, method, key formulas, figures and limitations; can read local Zotero items first and includes a glossary-card skill. Needs Python 3.10+ and PyMuPDF.

MathWorks' official toolkit for reading, building, modifying and testing Simulink models via the MATLAB MCP server, with skills for control design, Simscape, code generation and compliance checks. Needs licensed MATLAB R2023a+ and Simulink; run the official installer in MATLAB first.

LangChain's official skill collection: framework selection, quickstarts, middleware, persistence, human-in-the-loop approval, RAG and eval design across LangChain, LangGraph and Deep Agents, in Python and TypeScript. Also installable as a Claude Code plugin. Still in early development.

Plugin marketplace from obra, author of Superpowers: includes the superpowers engineering workflow, episodic-memory for searching past sessions, superpowers-chrome for browser control, elements-of-style writing guidance and more.

Connects agents to live Jupyter notebooks: read, write, insert and execute cells and read multimodal outputs like charts, for interactive data analysis. Bring your own JupyterLab or JupyterHub; open source, maintained by Datalayer.

Breaks a rough explanation idea into a scene-by-scene storyboard, then writes animation code following best practices for Manim Community or 3Blue1Brown's ManimGL, for math and physics explainers in class demos and educational videos. Needs Python, FFmpeg and LaTeX installed locally.