📦 mco-org/squad

Multi-Agent Terminal Collaboration with Squad

Squad is a collaborative tool that enables multiple AI CLI agents to communicate directly through a shared SQLite database without requiring any background processes or daemons. By installing a single slash command into tools like Claude Code, Gemini CLI, or Codex, users can assign distinct roles—such as manager, worker, or inspector—to separate terminal windows. Each agent operates independently, sending and receiving task updates through simple CLI commands while automatically resolving ID conflicts. This approach streamlines multi-agent workflows, allowing you to orchestrate complex projects by having specialized agents handle tasks, report results, and coordinate in real-time.

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📦 gamedev-skills/awesome-gamedev-agent-skills

Game Development Skills for AI Coding Agents

AI coding agents can now access sixty-six specialized game development skills through a single portable repository. This collection uses a master router that automatically detects your game engine and task to load only the specific instructions required for your build. By utilizing version-pinned skill files, it ensures compatibility across major platforms like Godot, Unity, Unreal, and various web engines. You can simply describe your objective in plain language and the system orchestrates the necessary knowledge without requiring manual configuration. This project streamlines complex development workflows, helping agents write accurate, engine-specific code to accelerate your game production from prototype to publish.

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📦 einsia/browser-bc

Turn Your Browser Actions into Reusable AI Skills

Local browser automation allows you to record free-form tasks that automatically distill into reusable AI skills. By capturing your interactions, the system atomizes and classifies website activities into capability buckets, which are then converted into durable instruction sets for Claude Desktop or Claude Code. This setup uses a local Python server to process your data privately, ensuring only the distillation calls leave your machine. Once configured, these skills provide actionable guidance or automated workflows within your browser environment. Ultimately, this project turns repetitive manual tasks into portable, structured knowledge that helps AI assistants execute complex web sequences efficiently.

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📦 techenthusiast167/deepsearch-

Automate OSINT with DeepSearch

DeepSearch is the Python utility that streamlines digital footprint analysis by automating complex Google search operators. This tool helps security researchers and investigators gather intelligence across social media, forums, and document repositories without manual effort. By applying over twenty-five specialized search parameters, it constructs targeted queries to map an individual's online presence quickly. It features an interactive console with color-coded progress tracking, optional browser automation to open results directly, and simple report generation for documentation. Whether you are conducting penetration testing or performing privacy audits, this utility provides a professional, time-saving way to uncover publicly available information effectively.

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📦 codag-megalith/codag-visualizer

Visualize Your AI Workflows Instantly

Codag is the visualizer that finally lets you see exactly how your AI code works by mapping complex LLM workflows into interactive graphs directly inside your editor. It analyzes your entire codebase to detect API calls, decision branches, and processing steps, solving the frustration of manually tracing nested tool calls or multi-agent pipelines. With support for major frameworks and languages, it updates your workflow maps in real-time as you edit and links every node back to your specific lines of source code. Master your agent logic today by giving your AI architecture the clarity it truly deserves.

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📦 itsthelore/wayfinder-router

Stop Overpaying for LLMs with Wayfinder

Wayfinder is the deterministic CLI tool that optimizes your AI costs by routing prompts to the right model size. It analyzes prompt structure and wording to decide instantly whether a request needs a small local model or a powerful cloud alternative. By eliminating the need for extra model calls or expensive API checks to determine routing, it ensures your decisions are entirely offline and sub-millisecond. You can easily calibrate it to your specific traffic and integrate it with any OpenAI-compatible client. Start using Wayfinder to automatically shift cheap tasks to local hardware and save your budget for the hard stuff.

📰 https://news.ycombinator.com/item?id=48704373

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📦 johannesjo/parallel-code

Run AI Coding Agents in Parallel with Git Worktrees

Dispatch multiple AI coding agents simultaneously by running them in isolated git worktrees. This open-source desktop application lets you deploy tools like Claude Code, Codex, and Gemini side by side without sequence blocking or version conflicts. It automatically sets up separate branches and directories for every task, allowing you to review diffs and merge successful changes while discarding others from a single unified interface. With keyboard-first controls and real-time progress monitoring, it streamlines complex development workflows by keeping your environment organized. Enhance your coding productivity by testing different agents on the same project in one afternoon.

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📦 tmdgusya/engineering-discipline

Automate Engineering Discipline in AI Coding Agents

Integrate structured engineering workflows into your AI coding agents to ensure every request moves from a vague idea to a verified, high-quality implementation. This project provides a chained skill system that automatically routes tasks based on complexity, forcing agents to clarify scopes, craft executable plans, and perform independent validation. It handles everything from small bug fixes using systematic debugging to multi-day projects requiring milestone orchestration and checkpoint recovery. By enforcing strict engineering protocols like information-isolated reviews and cleanup, you gain a more reliable, stable coding assistant that treats development with true technical discipline.

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📦 publicdotcom/publicdotcom-mcp-server

Trade Stocks With AI Using the Public.com MCP Server

The Public.com MCP Server is the Model Context Protocol implementation that finally lets your AI assistant directly manage your brokerage account. By wrapping the official trading API, this tool enables you to execute trades for stocks, crypto, and options using simple natural language commands. You can verify your portfolio, pull real-time market quotes, and place complex multi-leg orders without ever leaving your AI interface. It bridges the gap between your investments and intelligent automation by exposing read-only data and secure execution capabilities as standardized tools. Connect your account today to experience a more conversational approach to modern market trading.

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📦 vibheksoni/stealth-browser-mcp

stealth-browser-mcp

Bypass aggressive antibot systems like Cloudflare and grab pixel-perfect UI clones using your favorite AI chat. By running stealth-browser-mcp, your AI agent gains a massive ninety-seven-tool arsenal powered by nodriver and Chrome DevTools Protocol. It lets the AI write dynamic Python network hooks on the fly, intercept API payloads, and extract elements with over three hundred CSS properties, DOM structures, and raw assets intact. It even runs in a minimal twenty-tool mode to keep your chat clean. Fire up this server to give your AI actual stealth browsing superpower.

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📦 joeynyc/hermes-skins

hermes-skins

You can transform your Hermes command line interface from a standard terminal into a customized visual experience using hermes-skins. This project provides a collection of stylized themes that modify banner colors, response box labels, and custom ASCII art without altering the AI's core behavior. You can activate themes like the retro green phosphor Vault-Tec terminal, a pink-and-cyan Neonwave perspective grid, or the MS-DOS Norton Commander layout with its classic F-key shortcut bar. Customizing your setup is as simple as placing a single YAML file in your local directory to define your own hex colors, thinking verbs, and custom loading spinner faces. It is a brilliant way to bring classic computing...

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📦 mit-spark/daaam

Daaam

Build 3D Dynamic Scene Graphs on the fly with real-time semantic descriptions for robots. By combining SAM segmentation with BotSort tracking, this system continuously labels objects in 3D space. It solves the massive computational bottleneck of querying heavy multimodal models for every single camera frame. Instead of redundant calls, its assignment service runs a mixed-integer program to select only the most salient, non-overlapping frames before prompting a Describe Anything Model. You get highly accurate spatial-temporal memory without choking your hardware. Grab a ROS 2 workspace, hook up a depth camera, and let your robot map and understand its environment dynamically.

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📦 alisa0808/vibe-creating-skill

vibe-creating-skill

vibe-creating-skill is the open-source prompt-engineering skill that finally stops you from over-specifying technical camera parameters for video generation. Rather than cramming your prompts with useless lens sizes and shutter speeds, this portable agent skill translates your rough stories into model-ready prompts that focus entirely on emotion, tone, and visual anchors. It evaluates your input on three distinct axes, outputting a consistent four-part response containing a judgment, action, result, and notes. Compatible with agents like Claude Code, it prepares your concepts perfectly for text-to-video engines like Seedance. Try feeding your raw ideas to vibe-creating-skill and let the AI handle the heavy visual rendering.

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📦 walter-grace/mac-code

mac-code

You can now run a thirty-five billion parameter AI agent on a standard sixteen gigabyte Mac mini at thirty tokens per second without paying a dime in API fees. The mac-code project achieves this by running local models like Qwen three point five entirely on Apple Silicon. It features an innovative flash streaming architecture that pins critical attention weights in RAM while streaming massive feed-forward network weights directly from your SSD on a layer-by-layer basis. By bypassing the macOS page cache and utilizing expert-level streaming for mixture-of-experts models, it keeps memory usage completely flat. This gives you a private, zero-cost coding assistant right in your terminal.

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📦 agricidaniel/claude-repurpose

Automate Content Repurposing with Claude Code

Claude Repurpose is a specialized engine for Claude Code that transforms a single piece of content into over ten platform-optimized posts in seconds. By automatically extracting key insights, quotes, and statistics from YouTube videos, blog posts, or local files, it distributes your message across six parallel AI agents to ensure every output feels native to platforms like LinkedIn, Twitter, and TikTok. It goes beyond simple cross-posting by adapting character limits, formatting, and hooks based on current algorithmic benchmarks. This tool helps creators, marketers, and solopreneurs scale their reach efficiently, saving hours of manual labor while maintaining professional, high-engagement content standards.

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📦 kyutai-labs/pocket-tts

pocket-tts

This lightweight text-to-speech model runs entirely on your CPU and starts generating audio in just two hundred milliseconds. Called pocket-tts, it squeezes a high-quality speech synthesizer into a tiny one-hundred-million parameter footprint that uses only two CPU cores. Instead of relies on heavy GPUs or slow web APIs, you can run voice cloning and streaming audio locally at six times real-time speed on a basic MacBook Air. Under the hood, it pairs a transformer-based flow language model with the Mimi neural audio codec to synthesize natural speech. It is a brilliant piece of local-first engineering that makes on-device speech synthesis incredibly accessible.

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📦 bayramannakov/claude-reflect

claude-reflect

Your Claude Code CLI can now automatically learn from its mistakes and remember your preferences forever. The claude-reflect plugin uses a hybrid system of real-time regex matching and semantic AI validation to capture your corrections, positive feedback, and workflow patterns directly from your terminal sessions. Instead of repeating instructions, these captured learnings are automatically queued, reviewed, and synced into your CLAUDE.md files and memory rules. It even analyzes your session history to discover repeating tasks and draft custom reusable commands for you. Install claude-reflect to build a permanently smarter terminal assistant that adapts specifically to your development habits.

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📦 kageroumado/adrafinil

Adrafinil

Your Mac can bypass clamshell sleep and run tasks with the lid closed only when an active AI agent is actually working. Standard tools like caffeinate keep your machine wired forever, draining your battery in your bag, but adrafinil is a clever eugeroic for macOS. It uses a tiny root helper to toggle system sleep rules dynamically when agents like Claude Code or Cursor start a task, then completely steps aside the moment they finish. To keep your laptop safe, it features a built-in thermal cutout that forces sleep if your machine starts cooking. Grab this tool to keep your background tasks running safely.

📰 https://news.ycombinator.com/item?id=48701512

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📦 fakechris/obsidian_vault_pipeline

Obsidian Vault Pipeline

Your local Obsidian vault is no longer just a collection of static files. obsidian_vault_pipeline transforms your notes into an auditable knowledge state runtime using local intelligence. Instead of just searching your files, this system runs six structured pipeline stages: it ingests raw inputs like Pinboard links, GitHub repositories, and web clippings, compiles them into structured claims, evidence, and relations, and resolves internal contradictions. It then projects this processed knowledge into dynamic reader atlas pages, interactive graph views, and a local web interface. It makes your notes active, connected, and completely traceable. Check out this clever local pipeline to make your vault think.

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📦 nirdiamant/agent_memory_techniques

Agent Memory Techniques

Build smarter LLM agents that actually remember past conversations by exploring thirty runnable Jupyter notebooks filled with real Python code. The agent_memory_techniques repository solves the persistent problem of AI agents forgetting user context between sessions. It walks you through short-term conversation buffers, long-term vector stores, and cognitive structures like hierarchical memory layers. You can run code for advanced self-reflection patterns, episodic-to-semantic knowledge graph extraction with Graphiti, and frameworks like Mem0 or Letta. It is a highly practical playbook for anyone wanting to build personalized, long-lasting AI assistants that learn from every single interaction.

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