Showing 1607 open source projects for "no coding"

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    Ship Agents Faster

    Transform your applications and workflows into powerful agentic systems at global scale.

    Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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    MongoDB Atlas runs apps anywhere

    Deploy in 115+ regions with the modern database for every enterprise.

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  • 1
    Agent Skills

    Agent Skills

    Agent skills for designers and builders using Codex, Claude, Cursor

    Agent Skills is a curated library of reusable AI-agent workflows for designers, developers, and creative builders. Its skills are written as portable Markdown playbooks that can be loaded by Codex, Claude, Cursor, and other coding agents. The collection spans web design, game development, media workflows, automation, performance optimization, auditing, and prompt generation. Each skill focuses on procedural steps, useful defaults, guardrails, and acceptance checks instead of broad reference material. Optional folders can include scripts, assets, examples, articles, references, and runnable demos. ...
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  • 2
    Phone Harness

    Phone Harness

    Let your agent control your phone

    Phone Harness is a lightweight system that lets AI coding agents interact directly with a real iPhone through macOS iPhone Mirroring. It requires no jailbreak, Xcode project, WebDriverAgent, or custom software installed on the phone. Screenshots of the mirrored window provide visual input, while Apple's Vision framework extracts visible text and tap-ready coordinates. macOS CGEvents supply taps, long presses, drags, scrolling, keyboard input, and iPhone Mirroring shortcuts.
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  • 3
    ADR

    ADR

    ADR secures enterprise AI agents through observability

    ADR, short for Agentic AI Detection and Response, is an enterprise security system for monitoring and evaluating AI agents. It captures agent intent, tool activity, and execution traces from coding assistants, internal automations, and customer-facing agents. A normalized sensor layer provides observability across multiple agent tools and operating systems. ADR-Bench supplies more than 300 realistic tasks, 133 MCP servers, and coverage of 17 documented agent attack techniques. Its two-tier detector combines high-recall triage with deeper agentic analysis of suspicious sessions. ...
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  • 4
    SimpleEnglish

    SimpleEnglish

    Agent skill: make LLMs write docs in ASD-STE100

    SimpleEnglish is a portable agent skill that makes language models write technical documentation in ASD-STE100 Simplified Technical English. It replaces vague, promotional, and overly complex AI prose with short, direct, testable statements. The instructions enforce controlled practices such as active voice, simple tenses, consistent terminology, limited sentence length, and one instruction per sentence. It is designed for documentation, error messages, runbooks, incident reports, release...
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  • Fully Managed MySQL, PostgreSQL, and SQL Server Icon
    Fully Managed MySQL, PostgreSQL, and SQL Server

    Automatic backups, patching, replication, and failover. Focus on your app, not your database.

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  • 5
    Loop Library

    Loop Library

    A library of practical AI-agent loops and an installable skill

    Loop Library is a library and installable skill for designing repeatable AI-agent workflows. It is built around the idea of loops, which are bounded playbooks that tell an agent what to do, how to check progress, what to try next, and when to stop. The repository contains both a public loop library website and the Loopy skill that agents can use to discover, audit, adapt, run, and prepare loops. It helps turn open-ended prompts into measurable workflows with evidence, stopping criteria, and...
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  • 6
    Ralph

    Ralph

    Autonomous AI agent loop that runs until all PRD items are complete

    Ralph is an autonomous AI coding loop that repeatedly runs agentic development tools until every item in a product requirements document is complete. It is designed to work with Amp or Claude Code, launching a fresh AI instance on each iteration to avoid context overload. Instead of relying on one long conversation, Ralph keeps progress through git history, a structured prd.json file, and an append-only progress.txt memory file.
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  • 7
    Wandesk

    Wandesk

    Give intelligence shape. Let AI sculpt your desktop

    ...Built-in apps include Chat, Notebook, Ledger, Memory, Files, Tasks, Settings, Claude Code, Codex, and Open Source Radar. It is useful for users who want an AI workspace where apps, memory, and coding agents share context instead of living in separate chat threads.
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  • 8
    agents-best-practices

    agents-best-practices

    Provider-neutral Agent Skill for Codex, Claude Code

    ...It is built around the principle that the model proposes actions, while the harness validates, authorizes, executes, records, and returns observations. The project applies to coding agents, research agents, support agents, operations agents, sales agents, finance agents, healthcare agents, education agents, and workflow automation agents. It helps users reason about tool permissions, runtime discipline, observability, evaluation, and safer execution boundaries. The skill can also generate MVP blueprints for agent systems without tying the design to a single model provider. ...
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  • 9
    Guizang Social Card Skill

    Guizang Social Card Skill

    Claude Code / Codex skill — generate Xiaohongshu carousels

    ...It supports editorial magazine layouts and Swiss-style visual systems, giving agents rules for typography, spacing, covers, and page rhythm. The project is self-contained and meant to be used by AI coding or agent tools as a repeatable creative workflow. It is useful for creators, marketers, designers, and content teams producing platform-ready social visuals.
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    Host LLMs in Production With On-Demand GPUs

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  • 10
    TokenSpeed

    TokenSpeed

    TokenSpeed is a speed-of-light LLM inference engine

    ...It builds on ideas and components from the broader open-source inference ecosystem while presenting its own execution stack. TokenSpeed is useful for developers building local or server-side LLM infrastructure for agents, coding systems, and high-volume AI applications. Its main value is providing an inference layer optimized for fast token generation under practical agent workloads.
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  • 11
    Hallmark

    Hallmark

    Anti-AI-slop design skill for Claude Code, Cursor, and Codex

    Hallmark is an anti-AI-slop design skill for AI coding assistants such as Claude Code, Cursor, and Codex. It gives agents a concrete design rule set for producing interfaces that look intentionally crafted rather than generic, repetitive, or template-like. The project focuses on typography, color, layout, motion, microinteractions, visual hierarchy, and structural variation. It can be used to build new UI, audit existing code, or redesign an interface while keeping the underlying content and information architecture. ...
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  • 12
    GPTImage2Skill

    GPTImage2Skill

    GPT Image 2 prompt gallery, image prompt library, agentic skill

    GPTImage2Skill is a curated prompt gallery, agent skill, and command-line workflow for working with GPT Image 2 generation and editing. It provides reusable image prompts across creative, technical, academic, interface, design, photography, typography, gaming, anime, map, tattoo, and reference-editing use cases. The project is designed to help agents and users produce stronger visual outputs without starting from a blank prompt every time. Its gallery is organized into category files so an...
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  • 13
    Claude Code Skills & Plugins

    Claude Code Skills & Plugins

    232+ Claude Code skills & agent plugins for Claude Code, Codex

    Claude Skills is a repository that provides a collection of structured skill definitions designed to enhance the capabilities of Claude-based AI systems. Each skill encapsulates a specific capability, such as coding, analysis, or workflow execution, allowing the model to perform tasks more effectively. The project emphasizes modularity, enabling skills to be combined and reused across different contexts. It is designed to integrate seamlessly into AI workflows, providing a plug-and-play approach to extending functionality. The repository also includes examples and templates, making it easier for developers to create their own custom skills. ...
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  • 14
    pg-aiguide

    pg-aiguide

    MCP server and Claude plugin for Postgres skills and documentation

    pg-aiguide is a tool designed to enhance AI-assisted development with PostgreSQL by providing structured knowledge and skills directly to coding agents. It acts as a bridge between database documentation and AI tools, enabling more accurate generation of SQL queries and database interactions. The system integrates with Claude Code through an MCP server, allowing agents to access curated PostgreSQL knowledge in real time. It focuses on improving developer productivity by reducing errors and providing context-aware suggestions. ...
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  • 15
    k-skill

    k-skill

    Skill collection for Koreans - SRT, KTX, KakaoTalk, Hangul

    The k-skill project is an AI skill management framework designed to organize, structure, and execute reusable capabilities within AI-driven development environments. It focuses on defining skills as modular, composable units that can be invoked by agents to perform specific tasks such as coding, reasoning, or automation. The system provides a standardized structure for skills, enabling consistency across different workflows and improving interoperability between tools. It is designed to integrate with modern AI agent ecosystems, allowing developers to extend functionality without rewriting core logic. The project emphasizes simplicity and modularity, making it easier to manage large collections of skills in complex environments. ...
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  • 16
    GenericAgent

    GenericAgent

    Self-evolving autonomous agent framework

    ...It is designed around modularity, allowing developers to define agents with interchangeable components such as tools, memory systems, and reasoning strategies. The architecture emphasizes generality, enabling the same agent framework to be adapted for different domains including coding, research, and task automation. It integrates with modern language models to provide planning, execution, and iterative reasoning capabilities, making it suitable for complex workflows. The project also focuses on extensibility, allowing developers to plug in custom tools or APIs and tailor agent behavior to specific use cases. By abstracting common agent patterns, it reduces the overhead of building agent systems from scratch. ...
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  • 17
    LaReview

    LaReview

    The code review workbench

    LaReview is a developer-first, local-first code review workbench designed to transform complex pull requests or diffs into structured, high-signal review workflows powered by AI assistance. Instead of overwhelming developers with raw diffs or automated comment spam, the tool analyzes code changes and generates an intent-driven review plan that groups changes into logical flows such as authentication, API behavior, or data handling, and prioritizes them based on risk. It operates as a desktop...
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  • 18
    SynaBun

    SynaBun

    Persistent vector memory for AI assistants

    Synabun is an open-source AI memory management and augmentation system designed to provide persistent, semantic memory for AI agents and coding assistants, particularly those compatible with the MCP (Model Context Protocol) ecosystem. It functions as a local-first solution that stores and retrieves contextual knowledge across sessions using a built-in vector database powered by embeddings, eliminating the need for external APIs, cloud services, or Docker dependencies. The system integrates tightly with developer workflows by running alongside tools like Claude Code, enabling automatic memory capture, retrieval, and contextual augmentation through lifecycle hooks and commands. ...
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  • 19
    Startup

    Startup

    Startup is free Next.js template for SaaS startups

    ...The template includes all essential pages and sections required for a complete business website, such as landing pages, feature sections, blogs, and contact areas. It emphasizes clean, high-quality design and follows best practices in semantic coding, making it suitable for production use. The template also supports TypeScript, improving maintainability and developer experience in larger projects. Additional features like dark and light mode ensure adaptability to different user preferences and design requirements. Overall, Startup Next.js serves as a practical boilerplate that accelerates the creation of professional websites without requiring developers to design layouts from scratch.
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  • 20
    Clean Code concepts for .NET/.NET Core

    Clean Code concepts for .NET/.NET Core

    Clean Code concepts and tools adapted for .NET

    ...The repository covers topics such as naming conventions, code structure, error handling, and design patterns, emphasizing readability and long-term maintainability. It encourages developers to adopt disciplined coding habits that reduce technical debt and improve collaboration within teams. The content is structured in a way that allows both beginners and experienced developers to benefit from practical insights and actionable recommendations. It also highlights common pitfalls and anti-patterns, helping developers avoid mistakes in real-world scenarios.
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  • 21
    opencode.nvim

    opencode.nvim

    Integrate the opencode AI assistant with Neovim

    opencode.nvim is a Neovim plugin that integrates the opencode AI coding assistant directly into the editor, enabling developers to interact with AI agents in a deeply context-aware and workflow-native way. It allows users to send prompts that automatically include relevant editor context such as the current buffer, selected text, diagnostics, and visible content, making AI interactions far more precise and useful during development.
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  • 22
    Reflexion

    Reflexion

    Reflexion: Language Agents with Verbal Reinforcement Learning

    ...The framework introduces a mechanism where agents maintain a memory of past attempts and use that memory to guide future decisions, effectively simulating a learning process without requiring traditional model retraining. This approach is particularly useful for complex reasoning tasks, coding challenges, and decision-making scenarios where initial outputs may be incomplete or incorrect. Reflexion also emphasizes transparency by making intermediate reasoning steps explicit, allowing developers to inspect how conclusions are reached and where improvements occur.
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  • 23
    Streamdown

    Streamdown

    Streaming markdown renderer for AI apps with smooth updates

    ...Streamdown is built to handle partial Markdown input gracefully, progressively enhancing the output as more text becomes available. It is especially relevant for chat interfaces, coding assistants, and any environment where responses are streamed token by token. Streamdown emphasizes performance and simplicity, ensuring that developers can integrate it without unnecessary complexity. It prioritizes correctness in Markdown rendering while maintaining responsiveness during continuous updates. Overall, it serves as a practical solution for improving the user experience of real-time generated text displays.
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  • 24
    SemTools

    SemTools

    Semantic search and document parsing tools for the command line

    ...SemTools can parse documents, build semantic embeddings, and perform similarity searches across datasets, making it useful for research, knowledge management, and AI-assisted coding workflows. The toolkit is designed to work well with modern AI pipelines, particularly those involving large language models that require structured knowledge retrieval.
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  • 25
    Machine Learning Foundations

    Machine Learning Foundations

    Machine Learning Foundations: Linear Algebra, Calculus, Statistics

    ...The repository includes Jupyter notebooks with explanations and examples that demonstrate how these mathematical principles relate to real machine learning applications. Each section introduces theoretical concepts and then illustrates them through practical coding examples to reinforce understanding. The project is designed for students and practitioners who want to strengthen their foundational knowledge before working with more advanced machine learning frameworks.
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