#javascript
Figma MCP server connects your Figma designs to AI coding tools in VS Code, Cursor, Claude, and more, letting agents pull variables, components, and layouts to generate precise code from selected frames. You can write to Figma canvases, search design systems, and use Code Connect for codebase consistency. This speeds up design-to-code workflows, ensures UI matches designs exactly using your tokens, and cuts errors for faster, reliable app building.
https://github.com/figma/mcp-server-guide
Figma MCP server connects your Figma designs to AI coding tools in VS Code, Cursor, Claude, and more, letting agents pull variables, components, and layouts to generate precise code from selected frames. You can write to Figma canvases, search design systems, and use Code Connect for codebase consistency. This speeds up design-to-code workflows, ensures UI matches designs exactly using your tokens, and cuts errors for faster, reliable app building.
https://github.com/figma/mcp-server-guide
GitHub
GitHub - figma/mcp-server-guide: A guide on how to use the Figma MCP server
A guide on how to use the Figma MCP server. Contribute to figma/mcp-server-guide development by creating an account on GitHub.
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#python
AI Scientist-v2 is an autonomous AI system that generates research ideas, runs experiments, analyzes data, and writes full scientific papers using agentic tree search—no human templates needed. It produced the first entirely AI-written paper accepted via peer review at an ICLR workshop. You benefit by quickly exploring ML topics, automating discovery to save time and costs (about $20 per run on Linux with GPU), and scaling your research productivity for faster breakthroughs. Install via conda, set API keys, ideate with a Markdown file, then launch experiments. Run in a safe sandbox due to code risks.
https://github.com/SakanaAI/AI-Scientist-v2
AI Scientist-v2 is an autonomous AI system that generates research ideas, runs experiments, analyzes data, and writes full scientific papers using agentic tree search—no human templates needed. It produced the first entirely AI-written paper accepted via peer review at an ICLR workshop. You benefit by quickly exploring ML topics, automating discovery to save time and costs (about $20 per run on Linux with GPU), and scaling your research productivity for faster breakthroughs. Install via conda, set API keys, ideate with a Markdown file, then launch experiments. Run in a safe sandbox due to code risks.
https://github.com/SakanaAI/AI-Scientist-v2
GitHub
GitHub - SakanaAI/AI-Scientist-v2: The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search
The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search - SakanaAI/AI-Scientist-v2
#javascript
foobox is a sleek, customizable skin for foobar2000 music player that uses JSplitter for smooth layouts, lyrics, spectrum analyzer, playlists, covers, search, and online radio. Download the free Chinese version package from latest Releases—it works on 32/64-bit, installs green without the base app, and lets you switch layouts via Main Menu > View > Layout > Quick Setup. You get a modern, feature-rich interface that runs fast, giving full control over your music library for better listening.
https://github.com/dream7180/foobox-cn
foobox is a sleek, customizable skin for foobar2000 music player that uses JSplitter for smooth layouts, lyrics, spectrum analyzer, playlists, covers, search, and online radio. Download the free Chinese version package from latest Releases—it works on 32/64-bit, installs green without the base app, and lets you switch layouts via Main Menu > View > Layout > Quick Setup. You get a modern, feature-rich interface that runs fast, giving full control over your music library for better listening.
https://github.com/dream7180/foobox-cn
GitHub
GitHub - dream7180/foobox-cn: DUI é…Ťç˝® for foobar2000
DUI é…Ťç˝® for foobar2000. Contribute to dream7180/foobox-cn development by creating an account on GitHub.
#python #claude_code #guide #tutorial
Claude How To is a free GitHub guide (3,900+ stars) with visual tutorials, copy-paste templates, and a 11-13 hour learning path to master Claude Code features like slash commands, memory, skills, subagents, hooks, MCP, and plugins. Start in 15 minutes by cloning the repo and copying a command—build automated code reviews, deployments, and docs. You gain 10x productivity by combining features into real workflows, skipping basic docs for production-ready setups that save hours daily on grunt work.
https://github.com/luongnv89/claude-howto
Claude How To is a free GitHub guide (3,900+ stars) with visual tutorials, copy-paste templates, and a 11-13 hour learning path to master Claude Code features like slash commands, memory, skills, subagents, hooks, MCP, and plugins. Start in 15 minutes by cloning the repo and copying a command—build automated code reviews, deployments, and docs. You gain 10x productivity by combining features into real workflows, skipping basic docs for production-ready setups that save hours daily on grunt work.
https://github.com/luongnv89/claude-howto
GitHub
GitHub - luongnv89/claude-howto: A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy…
A visual, example-driven guide to Claude Code — from basic concepts to advanced agents, with copy-paste templates that bring immediate value. - luongnv89/claude-howto
#cplusplus #astronomy #data_visualization #planetarium #science #space #universe #visualization
OpenSpace is free, open-source software that lets you interactively explore the entire known universe on Windows or Linux computers, from planets and stars to galaxies, using real NASA data, simulations, and space missions like New Horizons. It works on screens, planetariums, or domes, supports custom content via Lua/Python, and enables global sharing. You benefit by easily visualizing cosmic data for fun, education, science projects, or stunning presentations without high costs.
https://github.com/OpenSpace/OpenSpace
OpenSpace is free, open-source software that lets you interactively explore the entire known universe on Windows or Linux computers, from planets and stars to galaxies, using real NASA data, simulations, and space missions like New Horizons. It works on screens, planetariums, or domes, supports custom content via Lua/Python, and enables global sharing. You benefit by easily visualizing cosmic data for fun, education, science projects, or stunning presentations without high costs.
https://github.com/OpenSpace/OpenSpace
GitHub
GitHub - OpenSpace/OpenSpace: This is the official GitHub repository for OpenSpace: an open source astrovisualization project.…
This is the official GitHub repository for OpenSpace: an open source astrovisualization project. For instructions on how to build and run OpenSpace, see the Getting Started Guides on the wiki page ...
#shell
Skills Public offers 16 reusable tools for Apple devs, like creating App Store notes from git, debugging iOS apps, fixing SwiftUI/React performance, running bug hunts, code reviews, and refactoring. Place skill folders in `$CODEX_HOME/skills` and check each `SKILL.md` for use. This saves you time on repeat tasks, boosts code quality, speeds debugging, and helps build better apps faster.
https://github.com/Dimillian/Skills
Skills Public offers 16 reusable tools for Apple devs, like creating App Store notes from git, debugging iOS apps, fixing SwiftUI/React performance, running bug hunts, code reviews, and refactoring. Place skill folders in `$CODEX_HOME/skills` and check each `SKILL.md` for use. This saves you time on repeat tasks, boosts code quality, speeds debugging, and helps build better apps faster.
https://github.com/Dimillian/Skills
GitHub
GitHub - Dimillian/Skills: My Codex Skills
My Codex Skills. Contribute to Dimillian/Skills development by creating an account on GitHub.
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#go #distribution_spec #helm #kubernetes #oci #oci_distribution #opencontainers #zot
Zot is a lightweight, production-ready OCI-native container registry for storing images, Helm charts, SBOMs, and other artifacts without vendor lock-in. It offers built-in authentication (OIDC, LDAP), storage options (S3, Azure), scanning, caching to cut Docker Hub limits/latency, and ARM/edge support as a single binary. You benefit by easily self-hosting a secure, scalable alternative to Docker Hub, saving costs, boosting speed, and enabling secret-less workflows on any device.
https://github.com/project-zot/zot
Zot is a lightweight, production-ready OCI-native container registry for storing images, Helm charts, SBOMs, and other artifacts without vendor lock-in. It offers built-in authentication (OIDC, LDAP), storage options (S3, Azure), scanning, caching to cut Docker Hub limits/latency, and ARM/edge support as a single binary. You benefit by easily self-hosting a secure, scalable alternative to Docker Hub, saving costs, boosting speed, and enabling secret-less workflows on any device.
https://github.com/project-zot/zot
GitHub
GitHub - project-zot/zot: zot - A scale-out production-ready vendor-neutral OCI-native container image/artifact registry (purely…
zot - A scale-out production-ready vendor-neutral OCI-native container image/artifact registry (purely based on OCI Distribution Specification) - project-zot/zot
#python #glm #image2text #ocr
GLM-OCR is a top 0.9B-parameter model for accurate OCR on complex documents like tables, code, formulas, seals, and receipts, scoring 94.62 on OmniDocBench V1.5. Install via `pip install glmocr`, use cloud API (no GPU needed) or self-host with vLLM/SGLang for fast, low-cost inference, and get JSON/Markdown outputs easily via CLI or Python. You benefit from quick, robust document parsing that saves time, cuts compute costs, and integrates simply into your apps for real-world tasks.
https://github.com/zai-org/GLM-OCR
GLM-OCR is a top 0.9B-parameter model for accurate OCR on complex documents like tables, code, formulas, seals, and receipts, scoring 94.62 on OmniDocBench V1.5. Install via `pip install glmocr`, use cloud API (no GPU needed) or self-host with vLLM/SGLang for fast, low-cost inference, and get JSON/Markdown outputs easily via CLI or Python. You benefit from quick, robust document parsing that saves time, cuts compute costs, and integrates simply into your apps for real-world tasks.
https://github.com/zai-org/GLM-OCR
GitHub
GitHub - zai-org/GLM-OCR: GLM-OCR: Accurate Ă— Fast Ă— Comprehensive
GLM-OCR: Accurate Ă— Fast Ă— Comprehensive. Contribute to zai-org/GLM-OCR development by creating an account on GitHub.
#typescript
OMX is a workflow layer that enhances OpenAI Codex by adding better task routing, reusable skills, and project state management. It keeps Codex as the execution engine while introducing canonical workflows like `$deep-interview` for clarification, `$ralplan` for planning approval, and `$ralph` or `$team` for execution. The benefit is that you get a structured, consistent approach to complex coding tasks—clarify intent first, approve the plan, then execute with either persistent single-owner loops or coordinated parallel work—without replacing Codex itself, just making your day-to-day work more organized and efficient.
https://github.com/Yeachan-Heo/oh-my-codex
OMX is a workflow layer that enhances OpenAI Codex by adding better task routing, reusable skills, and project state management. It keeps Codex as the execution engine while introducing canonical workflows like `$deep-interview` for clarification, `$ralplan` for planning approval, and `$ralph` or `$team` for execution. The benefit is that you get a structured, consistent approach to complex coding tasks—clarify intent first, approve the plan, then execute with either persistent single-owner loops or coordinated parallel work—without replacing Codex itself, just making your day-to-day work more organized and efficient.
https://github.com/Yeachan-Heo/oh-my-codex
GitHub
GitHub - Yeachan-Heo/oh-my-codex: OmX - Oh My codeX: Your codex is not alone. Add hooks, agent teams, HUDs, and so much more.
OmX - Oh My codeX: Your codex is not alone. Add hooks, agent teams, HUDs, and so much more. - Yeachan-Heo/oh-my-codex
#typescript #electron #open_source #pixijs #screen_capture #screen_recorder
OpenScreen is a free, open-source app like a simple Screen Studio for making beautiful product demos and screen walkthroughs. Record your full screen or windows, add zooms, mic/system audio, backgrounds, motion blur, annotations, trims, speed changes, and export in any ratio. Download from GitHub for macOS, Linux, or Windows—it's MIT-licensed so you can use, modify, or sell it freely with just a copyright notice. You save $29/month, get core tools without limits for personal/commercial use, and customize fully.
https://github.com/siddharthvaddem/openscreen
OpenScreen is a free, open-source app like a simple Screen Studio for making beautiful product demos and screen walkthroughs. Record your full screen or windows, add zooms, mic/system audio, backgrounds, motion blur, annotations, trims, speed changes, and export in any ratio. Download from GitHub for macOS, Linux, or Windows—it's MIT-licensed so you can use, modify, or sell it freely with just a copyright notice. You save $29/month, get core tools without limits for personal/commercial use, and customize fully.
https://github.com/siddharthvaddem/openscreen
GitHub
GitHub - siddharthvaddem/openscreen: Create stunning demos for free. Open-source, no subscriptions, no watermarks, and free for…
Create stunning demos for free. Open-source, no subscriptions, no watermarks, and free for commercial use. An alternative to Screen Studio. - siddharthvaddem/openscreen