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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.

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• Installing OpenWork on a personal computer
• Choosing an installer for the OS and CPU
• Setting up a work folder and model

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.

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• Prepare an STL model for a specific printer
• Slice models using existing material presets
• Check model size and print settings

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.

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• Designing conversational search for internal documents
• Planning RAG with a vector-enabled SQL database
• Hosting open models on GKE

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.

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• Create a PostgreSQL database on Google Cloud
• Connect to a database through Cloud SQL Auth Proxy
• Review database permissions and backup options

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.

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• Connecting Claude Code or Cursor to Google Ads
• Configuring API credentials and environment variables
• Testing campaign queries in natural language

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.

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• Getting an overview of an unfamiliar public repository
• Finding source paths for major components
• Understanding connections and data flow

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.

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• Preparing to work in an unfamiliar public codebase
• Understanding major components and their source paths
• Exploring component connections in an interactive diagram

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.

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• Discover papers beyond an exact keyword match
• Find research papers with open-source code
• Find papers from selected years or venues

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.

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• Setting up a first contribution to Superset
• Preparing a pull request for a Superset bug fix
• Discussing a feature proposal before implementation

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.

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• Comparing experiments with different training settings
• Viewing training metrics in a local dashboard
• Logging sample images and audio alongside metrics

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.

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• Investigate AI application problems using execution traces
• Evaluate answer quality across a test dataset
• Compare prompts and models through experiments

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.

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• Compressing a large language model into a smaller model
• Training a specialized model from teacher-generated examples
• Comparing distillation methods and training settings

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.

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• Import a skill from a GitHub URL
• Preview skill details before installation
• Install a skill from a specific branch, tag, or commit

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.

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• Review dependency licenses before shipping
• Assess a library before adding it
• Check license compatibility before releasing code

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.

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• Build a panel following WorldMonitor conventions
• Study patterns for scheduled data refreshes
• Review dashboard themes and grid layouts

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.

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• Mapping an organization's publicly exposed infrastructure
• Connecting public company records and social profiles
• Investigating image locations and video evidence

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.

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• Share a local HTML, CSS, or JavaScript experiment
• Prepare a README and a preview from the running project
• Publish a compatible web project on GitHub Pages

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.

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• Finding businesses by industry and location
• Building a list of local sales prospects
• Collecting business ratings and reviews

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.

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• Find code examples and open-source projects
• Search technical answers and GitHub Issues
• Explore developer news and discussions

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.

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• Assessing a designed binder against its target
• Predicting a protein and small-molecule complex
• Predicting complexes containing DNA or RNA

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.

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• Mapping an organization's externally exposed assets
• Recording evidence sources and confidence levels
• Prioritizing exposures within a limited research budget

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.

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• Analyzing experimental CSV data and saving plots
• Solving matrix equations and differential equations
• Analyzing signal frequencies and applying filters

Choose AI tools for literature searches, PDF conversion, citation-backed questions, and review writing. The skill also installs and runs supported tools through a shared launcher, with workflows that connect paper retrieval, conversion, and analysis.

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• Choosing tools for a literature review
• Converting research PDFs to Markdown
• Asking citation-backed questions across PDFs

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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