356 skills · sorted by relevance
Install the free OpenWork desktop app on macOS, Windows, or Linux using the appropriate download for the computer. Guide initial setup, folder authorization, model selection, and a first task such as summarizing local files.
Turn 3D models into printer instructions called G-code with OrcaSlicer. The skill selects existing printer and material presets, slices the model, and checks dimensions and output settings before handing over the files.
Design an enterprise search system that answers questions using retrieved company content, an approach called RAG. Gather requirements and produce architecture diagrams, deployment guidance, and validation plans using GKE, AlloyDB, and open models.
Create and connect to managed MySQL, PostgreSQL, or SQL Server databases on Google Cloud. This skill guides instance setup, database creation, access permissions, and connection steps, with references for backups, security, and Terraform configuration.
Set up the official Google Ads MCP Server, a connector that lets AI assistants retrieve campaign data and reporting metrics through natural language. The guide covers installation, credentials, client configuration, and connection checks.
Understand a public GitHub repository through GitDiagram's architecture overview. Get an explanation of its main components, source paths, and connections, plus Mermaid diagram source and an interactive diagram for exploring the code.
Explore how a public GitHub repository is organized using GitDiagram. Get explanations tied to component names and source paths, an interactive architecture diagram, and a narrated explainer video when one is available.
Use Gemini to discover research papers through related problems and alternative terminology. Results are organized into a table with publication details, code links, and short summaries, with filters for year, venue, and available code.
Prepare an open source contribution to Superset, from forking the code and setting up local development to running checks and opening a pull request. Follow repository rules and include evidence that the change works.
Use Phoenix to record execution traces, detailed records of an AI application's operations, and investigate problems. Evaluate answers on datasets, compare prompts and models, and set up monitoring through a self-hosted server.
Track machine learning experiments with SwanLab by recording training settings, metrics, and media such as images and audio. Learn to compare runs, inspect training charts, and connect existing training code to local, cloud, or self-hosted dashboards.
Guide knowledge distillation, where a smaller language model learns from a larger teacher. Covers training from teacher responses or prediction scores, adjusting training settings, and comparing outputs to support model compression and specialized training.
Install workspace skills from curated sources or GitHub, including bundled scripts, references, and assets. Preview a GitHub import, adapt its metadata to the workspace format, and load the installed skill immediately within the same run.
Review licenses in dependency lists, individual libraries, or code planned for public release. Get a memo covering obligations for the deployment model, license conflicts, unresolved questions, and recommended actions for legal review before shipping.
Use WorldMonitor’s architecture as a reference for building dashboards. Find examples of TypeScript panels, data services, grid layouts, API proxies, and refresh scheduling, with guidance on simplifying these patterns for a personal monitoring project.
Investigate organizations, domains, media locations, and cryptocurrency flows using open-source intelligence, or OSINT. The skill helps select relevant research tools, connect findings across sources, and preserve evidence with timestamps, screenshots, file hashes, and reproducible logs.
Package a finished local web project for GitHub with a tailored README and a preview from the running project. Audit files before pushing, publish compatible projects through GitHub Pages, and verify the repository and live demo.
Collect local business details, ratings, contact information, and requested reviews or emails from Google Maps. Guides users through running a local Docker scraper, validating searches, monitoring progress, and inspecting or organizing the results.
Search GitHub, Stack Overflow, Hacker News, and HuggingFace for code examples, projects, technical answers, discussions, models, datasets, and Spaces. Filter supported searches and receive structured JSON results containing titles, links, and snippets.
Use Boltz-2 to predict structures of complexes containing proteins, DNA, RNA, and small molecules. Obtain structure files and confidence scores to assess designed binders, with optional predictions of binding strength between a protein and a small molecule.
Structure open-source intelligence research, meaning investigation using publicly available information, for authorized external assessments. Map organizational assets, record evidence and confidence levels, prioritize exposures, and prepare reports that explain technical findings and business risks.
Write MATLAB or GNU Octave scripts for matrix calculations, data analysis, signal processing, and scientific plots. The skill also helps explain syntax and functions, convert code between MATLAB and Python, and run scripts when an interpreter is installed.
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文（用于「文献综述工具选型」与「一键安装/运行」）。
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MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
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