Search Results for "no code" - Page 6
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Showing 279 open source projects for "no code"
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Claude Scientific Skills
A set of ready to use Agent Skills for research, science, engineering
...Each skill bundles documentation, examples, and tool integrations so agents can reliably execute complex multi-step scientific workflows. The framework follows the open Agent Skills standard and works with multiple AI development environments including Claude Code, Cursor, and Codex. Its primary goal is to reduce the friction of scientific computing by giving AI agents structured access to specialized libraries, databases, and research pipelines. Overall, the repository acts as a modular capability layer that transforms general AI agents into domain-aware computational scientists. -
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Ars Contexta
Claude Code plugin that generates individualized knowledge systems
Ars Contexta is a Claude Code plugin designed to automatically transform conversations into structured, personalized knowledge systems that function as a “second brain.” Instead of leaving insights scattered across chat sessions, the tool captures how a user thinks, works, and solves problems, then converts those interactions into organized markdown files that the user fully owns. -
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Sandbox Agent
Run Coding Agents in Sandboxes
Sandbox Agent by Rivet is an experimental framework for running AI agents in controlled, isolated environments where they can safely execute code, interact with tools, and perform autonomous tasks without risking system integrity. It is designed to provide a secure sandbox that allows agents to test actions, manipulate files, and run commands while enforcing strict boundaries and monitoring capabilities. The project focuses on enabling more reliable and auditable agent behavior by separating execution from the host environment, which is especially important for applications involving automation, code generation, or system-level operations. ... -
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AWS Agent Skills
AWS Skills for Agents
...The skills cover critical AWS services such as IAM, Lambda, DynamoDB, S3, API Gateway, EKS, and many more, letting agents offer actionable advice on infrastructure as code, debugging, security configurations, and architectural workflows. Skills are kept up to date with weekly documentation checks, ensuring they reflect current AWS patterns and service changes. -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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AutoCoder
A long-running autonomous coding agent powered by the Claude Agent
...The core idea is to accelerate software production while preserving correctness and readability, minimizing the cognitive overhead that comes from switching between concept and implementation. Its architecture typically integrates language models with static analysis and template logic so that generated code is not only syntactically valid but also idiomatic and testable. -
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Skills Janitor
Audit, track usage, and compare your Claude Code skills
The Skills Janitor project is a lightweight plugin designed to manage, audit, and optimize AI agent skill ecosystems, particularly for environments like Claude Code and OpenAI Codex. It functions as a “maintenance layer” for AI skills by automatically scanning installed skill directories, identifying duplicates, and analyzing their structure and usage. One of its core purposes is to help developers maintain a clean and efficient skill environment, especially as the number of installed skills grows over time. ... -
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Build Your Own OpenClaw
A step-by-step guide to build your own AI agent
...The project is structured into 18 progressive stages, each introducing a new concept such as tool usage, memory persistence, event-driven design, and multi-agent coordination, with each step including both explanatory documentation and runnable code. It begins with foundational concepts like conversational loops and tool integration, then expands into more advanced capabilities such as dynamic skill loading, web interaction, and context management. As the tutorial progresses, it introduces architectural improvements including event-driven systems, WebSocket communication, and configuration hot-reloading to support scalability and real-time interaction. -
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Better Chatbot
Just a Better Chatbot. Powered by MCP Client & Workflows
Better‑chatbot is an AI chatbot framework powered by MCP protocols and workflows, allowing developers to deploy and integrate AI-powered chat systems with ease. Integrates all major LLMs: OpenAI, Anthropic, Google, xAI, Ollama, and more. MCP protocol, web search, JS/Python code execution, data visualization. Custom agents, visual workflows, artifact generation. Custom agents, visual workflows, artifact generation. Realtime voice chat with full MCP tool integration. -
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Wondel.ai Skills
Agent skills for Claude Code and other agentskills-compatible agents
Wondel.ai Skills is a repository that provides modular capability packages for AI agents, particularly those operating within Claude Code and similar ecosystems. Each skill represents a structured set of instructions, workflows, and tools that enable agents to perform specific tasks with expertise. These skills can cover a wide range of domains, including development, automation, and problem-solving, allowing agents to extend their capabilities dynamically. The system emphasizes modularity, enabling skills to be reused and combined into more complex workflows. ... -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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Desloppify
Agent harness to make your slop code well-engineered and beautiful
Desloppify is a utility-focused project aimed at improving the quality, structure, and clarity of generated or written text by removing redundancy, noise, and unnecessary verbosity. It is designed to “clean up” outputs, particularly those produced by AI systems, making them more concise, readable, and professional. The system likely applies heuristics or transformation rules to identify repetitive patterns, filler content, and stylistic inconsistencies. This makes it especially useful in... -
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Skyvern
Automate browser-based workflows with LLMs and Computer Vision
...Skyvern's AI decisions come with built-in explanations, providing clear summaries and justifications for every action. Support for proxies, with support for country, state, or even precise zip-code level targeting. Skyvern understands how to solve CAPTCHAs to complete complicated workflows. Support for authenticating into user accounts, including support for 2FA/TOTP. Extract data from workflows in any schema of your choice including CSV or JSON. Automate procurement pipelines, breeze through government forms, and complete workflows in any language. -
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forkd
Fork() for AI agent microVMs
...Instead of cold-booting a separate virtual machine for every worker, it forks children from a warmed parent snapshot and uses copy-on-write behavior to share the initial memory state. This makes it useful for spawning many isolated agent environments quickly during parallel research, testing, or code execution. The project is focused on runtime performance, sandbox isolation, and efficient branching from a live or prepared VM state. It is especially relevant for developers building agent infrastructure where many short-lived execution branches need to run safely. forkd is best understood as a low-level systems tool for scalable, isolated AI-agent workloads. -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
AutoAgent is a fully automated, zero-code LLM agent framework that lets users create agents and workflows using natural language instead of manual coding and configuration. It is structured around modes that cover both “use” and “build” scenarios: a user mode for running a ready-made multi-agent research assistant, plus editors for creating individual agents or multi-agent workflows from conversational requirements. -
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LazyCodex
The one and only agent harness for complex codebases
...It supports project memory so context can persist across sessions and decisions do not need to be repeatedly reintroduced. LazyCodex also emphasizes verified completion, which means the workflow is built around checking whether tasks are actually finished rather than only generating code. Its main value is turning Codex into a more disciplined coding agent environment for larger and more demanding repositories. -
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notebooklm-py
Unofficial Python API and agentic skill for Google NotebookLM
notebooklm-py is an unofficial Python API and agent-ready integration layer for Google NotebookLM that exposes NotebookLM functionality through code, the command line, and AI agent workflows. Its goal is to provide programmatic access not just to standard notebook operations, but also to many capabilities that are either limited or unavailable in the web interface, making it especially useful for automation and custom pipelines. The project covers notebook management, source ingestion, conversational querying, research workflows, and sharing controls, while also enabling the generation of a wide range of study and media artifacts. ... -
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agentmemory
#1 Persistent memory for AI coding agents
agentmemory is a persistent memory server for AI coding agents that captures project context, past decisions, bugs, preferences, and implementation details so users do not have to re-explain the same information in every session. It works across tools such as Claude Code, Cursor, Gemini CLI, Codex CLI, OpenCode, Cline, and any client that supports MCP or REST APIs. The system automatically records what agents do, compresses that activity into searchable memory, and injects relevant context when a new coding session begins. It combines keyword search, vector search, confidence scoring, lifecycle management, and knowledge graph querying to retrieve useful memories without overloading the context window. ... -
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designlang
Extract any website's complete design system with one command
...The tool supports exporting to frameworks like Tailwind, SwiftUI, Flutter, and WordPress, making it highly versatile for cross-platform development. It also integrates with tools like Figma and shadcn, enabling seamless design-to-code workflows. The system includes accessibility analysis features, such as WCAG compliance checks and CSS health audits, helping developers improve usability and standards compliance. It can be used via CLI or browser extension, making it flexible for different workflows. Overall, design-extract automates the process of reverse-engineering design systems, significantly accelerating frontend development. -
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Evolver
The GEP-Powered Self-Evolution Engine for AI Agents
...It also depends on Git as part of its operating model, using repository state for rollback, blast-radius calculation, and solidification workflows, which makes it especially relevant for code-centric agent environments. The CLI integrates with external agent runtimes through setup hooks, including support for platforms such as Cursor, where hooks can fire at specific lifecycle moments like session start or after file edits. -
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OpenAI Agent Skills
Skills Catalog for Codex
...It organizes reusable, task-specific workflows, instructions, scripts, and resources into modular skill folders so that an AI agent can reliably perform complex tasks without repeated custom prompting, making agent behavior more predictable and composable. Each skill is defined with clear metadata and instructions organizing how an AI assistant should complete specific tasks ranging from project management to code generation and documentation assistance. The repository supports community contributions, allowing developers to add new skills or update existing ones to keep the catalog relevant and practical for evolving use cases. -
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NullClaw
Fastest, smallest, and fully autonomous AI assistant infrastructure
...Despite its size, it delivers a complete AI stack with 22+ model providers, 18+ communication channels, integrated tools, hybrid memory, and sandboxed runtime support. Its architecture is fully modular, using vtable interfaces that allow providers, channels, tools, memory backends, and runtimes to be swapped without code changes. NullClaw is secure by design, enforcing pairing-based authentication, strict sandboxing, encrypted secrets, resource limits, and workspace scoping by default. Designed for portability and independence, it supports OpenAI-compatible APIs, multiple tunnels, hardware peripherals, and edge deployments including WASM-based logic. -
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AI Maestro
Give AI Agents superpowers: memory search, code graph queries
AI Maestro is a framework designed to orchestrate AI workflows and coordinate multiple components into cohesive systems. It focuses on enabling structured interaction between different AI modules, allowing them to collaborate on complex tasks. The system emphasizes modular design, enabling developers to build workflows by combining independent components. It supports automation, allowing tasks to be executed with minimal manual intervention. The framework is designed to be flexible,... -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
The project is the codebase for an AI agent named Cicero developed by Facebook Research. It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. ... -
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agents.md
A simple, open format for guiding coding agents
...The idea is that AGENTS.md acts as a “README for agents”: a predictable, structured place where humans can put instructions, conventions, build/test commands, environment setup, and other guidance that generative agents (e.g. code-writing, code-assisting tools) should consult when operating in the repo. Instead of putting everything in README or doc files (which are more human-oriented and might mix high-level narrative), AGENTS.md is intended to surface agent-relevant details that help them “do the right thing” (tests, style, project structure, tooling). -
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Claude Codex Settings
My personal Claude Code and OpenAI Codex setup
Claude Codex Settings is a configuration-focused repository that provides curated settings, prompts, and workflow optimizations for improving AI-assisted coding environments. It is designed to help developers fine-tune how Claude and similar models behave within coding workflows, ensuring more consistent and high-quality outputs. The project emphasizes practical usability, offering ready-to-use configurations that can be directly integrated into development environments. It also includes...