Trending on Aug 13, 2026
14 of 14 repositories
1.cathrynlavery/diagram-design
Editorial diagram design for Claude Code, Codex, GitHub Copilot, Cursor, Factory Droid, Qoder, and Pi. 45 diagram types. Self-contained HTML + SVG. No shadows. No Mermaid slop.
AI summary: A programmatic diagramming tool using a declarative schema to auto-generate beautiful system architectures.
60,855+2,855 stars that daydeveloper-toolsHTMLMIT2.macro-inc/macro
Macro is a unified workspace for teams: email, chat, docs, tasks, agents, calls, and CRM — @-linked together with shared AI memory.
AI summary: A unified workspace combining email, messaging, docs, tasks, and CRM into a single computable graph.
4,924+227 stars that dayproductivityRustAGPL-3.03.stablyai/orca
Orca is the place for working with a fleet of agents (e.g. Grok Bot, Claude Code). Run any coding agent with your own subscription. Available on desktop, mobile and remote runtime.
AI summary: An AI orchestrator enabling developers to run multiple autonomous coding agents simultaneously in parallel worktrees.
105,859+1,235 stars that daydeveloper-toolsTypeScriptMIT4.shiyu-coder/Kronos
Kronos: A Foundation Model for the Language of Financial Markets
AI summary: First open-source foundation model designed specifically for analyzing financial candlesticks and market data.
43,453+266 stars that dayai-mlPythonMIT5.hugohe3/ppt-master
AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio narration from speaker notes, and support for your own .pptx templates. · by Hugo He
AI summary: An automated tool that generates professional PowerPoint presentations directly from markdown text or structured data.
68,069+476 stars that dayproductivityPythonMIT6.infiniflow/ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
AI summary: An open-source RAG engine for enterprise that provides deep document understanding and verifiable AI responses.
92,857+139 stars that dayai-mlGoApache-2.07.paperclipai/paperclip
The open-source app everyone uses to manage agents at work
AI summary: A lightweight AI agent designed to operate specifically within codebases and browser environments.
107,303+571 stars that daydeveloper-toolsTypeScriptMIT8.NVIDIA-NeMo/Switchyard
Switchyard lets LLM applications route traffic across models and providers while preserving native OpenAI and Anthropic API compatibility - enabling flexible model selection, benchmarking, and cost/performance optimization.
AI summary: A fast Rust proxy and routing library for transparently translating and directing LLM traffic.
3,441+421 stars that dayinfrastructureRustApache-2.09.ZuodaoTech/everyone-can-use-english
人人都能用英语
AI summary: A structured methodology and resources for Chinese speakers to master English.
39,232+86 stars that daylearningTypeScriptGPL-3.010.smicallef/spiderfoot
SpiderFoot automates OSINT for threat intelligence and mapping your attack surface.
AI summary: An automated OSINT reconnaissance tool that gathers intelligence on targets from numerous sources.
23,720+74 stars that daysecurityPythonMIT11.localsend/localsend
An open-source cross-platform alternative to AirDrop
AI summary: Secure, cross-platform local network file and message sharing via REST API without requiring an internet connection.
95,590+213 stars that dayproductivityDartApache-2.012.Lightricks/LTX-2
Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.
AI summary: An advanced open-source video generation model with sophisticated temporal, spatial, and audio synthesis capabilities.
9,862+65 stars that dayai-mlPythonOther13.embabel/embabel-agent
Agent framework for the JVM. Pronounced Em-BAY-bel /ɛmˈbeɪbəl/
AI summary: An intelligent agent framework for the JVM, bringing high-level composability and testing to LLM applications.
4,532+40 stars that dayai-mlKotlinApache-2.014.cactus-compute/needle
Automation foundation model for tiny devices: 2-bit, 8-29 MB, tool calls, ASR, structured extraction and embeddings on phones, wearables, smart homes, robots, cars and microcontrollers.
AI summary: A 26M parameter Simple Attention Network optimized for function calling.
14,262+315 stars that dayai-mlPythonApache-2.0