Roam is a tool that builds a semantic graph of your codebase and allows AI agents to query it with one shell command. It pre-indexes your codebase into a semantic graph stored in a local SQLite DB, providing architecture-level graph queries offline, cross-language, and compact. Roam understands functions, modules, tests coverage, and overall architecture structure. It is best suited for agent-assisted coding, large codebases, architecture governance, safe refactoring, and multi-repo projects. Roam is not suitable for real-time type checking, dynamic/runtime analysis, small scripts, or pure text search. It offers speed, dependency-awareness, LLM-optimized output, fully local operation, and CI readiness.

Shodh-Memory is a cognitive memory system designed for AI agents to persist memory across sessions, learn from experience, and run entirely offline. It features Hebbian learning, activation decay, and semantic consolidation, packed into a single ~17MB binary. Users can deploy it on cloud, edge devices, or air-gapped systems to enhance the memory capabilities of AI agents.

sf-skills is a collection of reusable skills for Agentic Salesforce Development, enabling AI-powered code generation, validation, testing, debugging, and deployment. It includes skills for development, quality, foundation, integration, AI & automation, DevOps & tooling. The installation process is newbie-friendly and includes an installer script for various CLIs. The skills are compatible with platforms like Claude Code, OpenCode, Codex, Gemini, Amp, Droid, Cursor, and Agentforce Vibes. The repository is community-driven and aims to strengthen the Salesforce ecosystem.

llm.nvim is a universal plugin for a large language model (LLM) designed to enable users to interact with LLM within neovim. Users can customize various LLMs such as gpt, glm, kimi, and local LLM. The plugin provides tools for optimizing code, comparing code, translating text, and more. It also supports integration with free models from Cloudflare, Github models, siliconflow, and others. Users can customize tools, chat with LLM, quickly translate text, and explain code snippets. The plugin offers a flexible window interface for easy interaction and customization.

Pipelock is an all-in-one security harness designed for AI agents, offering control over network egress, detection of credential exfiltration, scanning for prompt injection, and monitoring workspace integrity. It utilizes capability separation to restrict the agent process with secrets and employs a separate fetch proxy for web browsing. The tool runs a 7-layer scanner pipeline on every request to ensure security. Pipelock is suitable for users running AI agents like Claude Code, OpenHands, or any AI agent with shell access and API keys.

PAIML MCP Agent Toolkit (PMAT) is a zero-configuration AI context generation system with extreme quality enforcement and Toyota Way standards. It allows users to analyze any codebase instantly through CLI, MCP, or HTTP interfaces. The toolkit provides features such as technical debt analysis, advanced monitoring, metrics aggregation, performance profiling, bottleneck detection, alert system, multi-format export, storage flexibility, and more. It also offers AI-powered intelligence for smart recommendations, polyglot analysis, repository showcase, and integration points. PMAT enforces quality standards like complexity ≤20, zero SATD comments, test coverage >80%, no lint warnings, and synchronized documentation with commits. The toolkit follows Toyota Way development principles for iterative improvement, direct AST traversal, automated quality gates, and zero SATD policy.

EVE is an official PyTorch implementation of Unveiling Encoder-Free Vision-Language Models. The project aims to explore the removal of vision encoders from Vision-Language Models (VLMs) and transfer LLMs to encoder-free VLMs efficiently. It also focuses on bridging the performance gap between encoder-free and encoder-based VLMs. EVE offers a superior capability with arbitrary image aspect ratio, data efficiency by utilizing publicly available data for pre-training, and training efficiency with a transparent and practical strategy for developing a pure decoder-only architecture across modalities.

Backlog.md is a Markdown-native Task Manager & Kanban visualizer for any Git repository. It turns any folder with a Git repo into a self-contained project board powered by plain Markdown files and a zero-config CLI. Features include managing tasks as plain .md files, private & offline usage, instant terminal Kanban visualization, board export, modern web interface, AI-ready CLI, rich query commands, cross-platform support, and MIT-licensed open-source. Users can create tasks, view board, assign tasks to AI, manage documentation, make decisions, and configure settings easily.

Gollama is a tool designed for managing Ollama models through a Text User Interface (TUI). Users can list, inspect, delete, copy, and push Ollama models, as well as link them to LM Studio. The application offers interactive model selection, sorting by various criteria, and actions using hotkeys. It provides features like sorting and filtering capabilities, displaying model metadata, model linking, copying, pushing, and more. Gollama aims to be user-friendly and useful for managing models, especially for cleaning up old models.

The 'Everything Claude Code' repository is a comprehensive collection of production-ready agents, skills, hooks, commands, rules, and MCP configurations developed over 10+ months. It includes guides for setup, foundations, and philosophy, as well as detailed explanations of various topics such as token optimization, memory persistence, continuous learning, verification loops, parallelization, and subagent orchestration. The repository also provides updates on bug fixes, multi-language rules, installation wizard, PM2 support, OpenCode plugin integration, unified commands and skills, and cross-platform support. It offers a quick start guide for installation, ecosystem tools like Skill Creator and Continuous Learning v2, requirements for CLI version compatibility, key concepts like agents, skills, hooks, and rules, running tests, contributing guidelines, OpenCode support, background information, important notes on context window management and customization, star history chart, and relevant links.

The AI Dev Kit is a comprehensive toolkit designed to enhance AI-driven development on Databricks. It provides trusted sources for AI coding assistants like Claude Code and Cursor to build faster and smarter on Databricks. The kit includes features such as Spark Declarative Pipelines, Databricks Jobs, AI/BI Dashboards, Unity Catalog, Genie Spaces, Knowledge Assistants, MLflow Experiments, Model Serving, Databricks Apps, and more. Users can choose from different adventures like installing the kit, using the visual builder app, teaching AI assistants Databricks patterns, executing Databricks actions, or building custom integrations with the core library. The kit also includes components like databricks-tools-core, databricks-mcp-server, databricks-skills, databricks-builder-app, and ai-dev-project.

Superset is a turbocharged terminal that allows users to run multiple CLI coding agents simultaneously, isolate tasks in separate worktrees, monitor agent status, review changes quickly, and enhance development workflow. It supports any CLI-based coding agent and offers features like parallel execution, worktree isolation, agent monitoring, built-in diff viewer, workspace presets, universal compatibility, quick context switching, and IDE integration. Users can customize keyboard shortcuts, configure workspace setup, and teardown, and contribute to the project. The tech stack includes Electron, React, TailwindCSS, Bun, Turborepo, Vite, Biome, Drizzle ORM, Neon, and tRPC. The community provides support through Discord, Twitter, GitHub Issues, and GitHub Discussions.

GPT-Load is a high-performance, enterprise-grade AI API transparent proxy service designed for enterprises and developers needing to integrate multiple AI services. Built with Go, it features intelligent key management, load balancing, and comprehensive monitoring capabilities for high-concurrency production environments. The tool serves as a transparent proxy service, preserving native API formats of various AI service providers like OpenAI, Google Gemini, and Anthropic Claude. It supports dynamic configuration, distributed leader-follower deployment, and a Vue 3-based web management interface. GPT-Load is production-ready with features like dual authentication, graceful shutdown, and error recovery.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

Cactus is an energy-efficient and fast AI inference framework designed for phones, wearables, and resource-constrained arm-based devices. It provides a bottom-up approach with no dependencies, optimizing for budget and mid-range phones. The framework includes Cactus FFI for integration, Cactus Engine for high-level transformer inference, Cactus Graph for unified computation graph, and Cactus Kernels for low-level ARM-specific operations. It is suitable for implementing custom models and scientific computing on mobile devices.

New API is a next-generation large model gateway and AI asset management system that provides a wide range of features, including a new UI interface, multi-language support, online recharge function, key query for usage quota, compatibility with the original One API database, model charging by usage count, channel weighted randomization, data dashboard, token grouping and model restrictions, support for various authorization login methods, support for Rerank models, OpenAI Realtime API, Claude Messages format, reasoning effort setting, content reasoning, user-specific model rate limiting, request format conversion, cache billing support, and various model support such as gpts, Midjourney-Proxy, Suno API, custom channels, Rerank models, Claude Messages format, Dify, and more.

Glimpse is a blazingly fast tool for peeking at codebases, offering features like fast parallel file processing, tree-view of codebase structure, source code content viewing, token counting with multiple backends, configurable defaults, clipboard support, customizable file type detection, .gitignore respect, web content processing with Markdown conversion, Git repository support, and URL traversal with configurable depth. It supports token counting using Tiktoken or HuggingFace tokenizer backends, helping estimate context window usage for large language models. Glimpse can process local directories, multiple files, Git repositories, web pages, and convert content to Markdown. It offers various options for customization and configuration, including file type inclusions/exclusions, token counting settings, URL processing settings, and default exclude patterns. Glimpse is suitable for developers and data scientists looking to analyze codebases, estimate token counts, and process web content efficiently.

PAIML MCP Agent Toolkit (PMAT) is a zero-configuration AI context generation system with extreme quality enforcement and Toyota Way standards. It allows users to analyze any codebase instantly through CLI, MCP, or HTTP interfaces. The toolkit provides features such as technical debt analysis, advanced monitoring, metrics aggregation, performance profiling, bottleneck detection, alert system, multi-format export, storage flexibility, and more. It also offers AI-powered intelligence for smart recommendations, polyglot analysis, repository showcase, and integration points. PMAT enforces quality standards like complexity ≤20, zero SATD comments, test coverage >80%, no lint warnings, and synchronized documentation with commits. The toolkit follows Toyota Way development principles for iterative improvement, direct AST traversal, automated quality gates, and zero SATD policy.

Smithers is a tool for declarative AI workflow orchestration using React components. It allows users to define complex multi-agent workflows as component trees, ensuring composability, durability, and error handling. The tool leverages React's re-rendering mechanism to persist outputs to SQLite, enabling crashed workflows to resume seamlessly. Users can define schemas for task outputs, create workflow instances, define agents, build workflow trees, and run workflows programmatically or via CLI. Smithers supports components for pipeline stages, structured output validation with Zod, MDX prompts, validation loops with Ralph, dynamic branching, and various built-in tools like read, edit, bash, grep, and write. The tool follows a clear workflow execution process involving defining, rendering, executing, re-rendering, and repeating tasks until completion, all while storing task results in SQLite for fault tolerance.

GitVizz is an AI-powered repository analysis tool that helps developers understand and navigate codebases quickly. It transforms complex code structures into interactive documentation, dependency graphs, and intelligent conversations. With features like interactive dependency graphs, AI-powered code conversations, advanced code visualization, and automatic documentation generation, GitVizz offers instant understanding and insights for any repository. The tool is built with modern technologies like Next.js, FastAPI, and OpenAI, making it scalable and efficient for analyzing large codebases. GitVizz also provides a standalone Python library for core code analysis and dependency graph generation, offering multi-language parsing, AST analysis, dependency graphs, visualizations, and extensibility for custom applications.

Roam is a tool that builds a semantic graph of your codebase and allows AI agents to query it with one shell command. It pre-indexes your codebase into a semantic graph stored in a local SQLite DB, providing architecture-level graph queries offline, cross-language, and compact. Roam understands functions, modules, tests coverage, and overall architecture structure. It is best suited for agent-assisted coding, large codebases, architecture governance, safe refactoring, and multi-repo projects. Roam is not suitable for real-time type checking, dynamic/runtime analysis, small scripts, or pure text search. It offers speed, dependency-awareness, LLM-optimized output, fully local operation, and CI readiness.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.