Search Results for "feedback"
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Showing 39 open source projects for "feedback"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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UI-TARS Desktop
A GUI Agent app based on UI-TARS to control your computer using AI
...This cross-platform tool supports both Windows and macOS, allowing users to perform tasks through intuitive commands. Key features include screenshot-based visual recognition, precise mouse and keyboard control, and real-time feedback on actions. Provides immediate responses and visual feedback on actions performed. The application facilitates seamless interaction with the computer, enhancing user experience by simplifying complex operations into straightforward language instructions. Leverages advanced AI to bridge the gap between visual elements and language commands. ... -
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Claude Code
Claude Code is an agentic coding tool that lives in your terminal
...Claude Code integrates seamlessly into your terminal, IDE, or GitHub by tagging @claude to interact with your code context. The tool is designed to simplify development by automating repetitive work and providing instant clarifications on code behavior. User feedback and usage data are collected responsibly, with strict privacy safeguards and limited retention, ensuring no feedback is used to train generative models. Claude Code is open and actively maintained with community-driven bug reporting and feature requests. Its natural language interface makes advanced coding workflows accessible without leaving your coding environment. -
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PentestGPT
Automated Penetration Testing Agentic Framework Powered by LLMs
...The platform supports multiple penetration testing categories, including web security, cryptography, reversing, forensics, privilege escalation, and binary exploitation. PentestGPT runs in a Docker-first environment, providing a secure, reproducible setup with built-in tooling and session persistence. It offers real-time feedback and live walkthroughs, allowing users to observe each step of the testing process as it unfolds. Built with a modular and extensible architecture, PentestGPT supports cloud and local LLMs, making it suitable for research, education, and authorized security testing. -
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OpenClaw-RL
Train any agents simply by 'talking'
...The project focuses on enabling agents to improve their behavior through interactive learning rather than relying solely on static prompts or predefined skills. One of its key ideas is allowing users to train an AI agent simply by interacting with it conversationally, using natural language feedback to guide the learning process. The system incorporates reinforcement learning techniques to refine the agent’s policies for tool use, decision making, and task completion over time. It also explores approaches such as online policy distillation and hindsight feedback signals to strengthen training signals from real interactions. ... -
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Personal AI Infrastructure
Agentic AI Infrastructure for magnifying HUMAN capabilities
Personal AI Infrastructure (PAI) is an ambitious open-source project focused on building a deeply personalized agentic AI system that learns from every interaction to magnify human capabilities across tasks and workflows. Unlike once-stateless chatbots, this platform captures context, memory, goals, preferences, and feedback to enable an AI that understands you and improves over time, using a full agentic stack rather than simple question-answer loops. PAI blends tools like browsing, code editing, execution, and more into a continuous Observe → Think → Plan → Execute → Verify → Learn cycle, letting the system refine its behavior with each use. Its architecture supports long-term memory, verification of actions, and ongoing self-improvement, blurring the line between “assistant” and persistent, evolving collaborator. -
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Mercury Agent
Soul-driven AI agent with permission-hardened tools, token budgets
...It focuses on orchestrating tasks across multiple tools and services, enabling agents to perform end-to-end operations. The system includes mechanisms for planning, execution, and feedback, allowing agents to refine their actions iteratively. It supports integration with external APIs and services, making it adaptable to various domains. The architecture is modular, allowing developers to customize and extend agent capabilities. It is particularly useful for automation, research, and task delegation scenarios. Overall, mercury-agent enables scalable and intelligent workflow automation. -
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Open Interface
Control Any Computer Using LLMs
...By sending user requests to an LLM backend, it determines the necessary steps and executes them by simulating keyboard and mouse inputs. The system can adjust its actions based on real-time feedback, providing a self-driving computer experience. -
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clawchief
Turn your OpenClaw into a Chief of Staff
...This approach allows for more predictable and organized multi-agent behavior compared to decentralized systems. The architecture likely includes task planning, delegation logic, and feedback loops that enable iterative refinement of outputs. It is particularly useful in scenarios where multiple agents must collaborate on interdependent tasks, such as coding, research, or automation pipelines. The system may also include monitoring tools to track agent performance and identify failures or inefficiencies. -
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MetaClaw
Just talk to your agent
MetaClaw is an AI or agent-oriented system that appears to focus on advanced control, coordination, or training of autonomous agents, potentially within reinforcement learning or tool-using environments. The project likely emphasizes meta-level reasoning, where agents are not only executing tasks but also adapting their strategies based on feedback and performance signals. It may incorporate mechanisms for learning from interactions, improving decision-making over time, and generalizing across different domains. The architecture suggests scalability, allowing the system to handle multiple agents or complex workflows simultaneously. It is likely designed for experimentation with next-generation agent systems that combine planning, learning, and execution. ... -
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Pro Workflow
Claude Code learns from your corrections: self-correcting memory
Pro Workflow is a productivity framework for Claude Code that introduces self-improving workflows through memory, context engineering, and structured agent orchestration. The system learns from user corrections over time, storing feedback and refining its behavior across sessions to improve accuracy and efficiency. It supports advanced development setups such as parallel worktrees, enabling multiple tasks to be handled simultaneously without interference. The framework includes a collection of prebuilt skills and workflows that have been tested in real-world scenarios, providing a strong starting point for developers. ... -
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AutoCoder
A long-running autonomous coding agent powered by the Claude Agent
...Rather than hand-writing boilerplate or repetitive patterns, users supply a specification—such as a description of a feature, a function prototype, or a module outline—and Autocoder fills in complete implementations that compile and run. It is built to support iterative refinement: after generating an initial draft, you can provide feedback or corrections, and the system will adjust the output to match evolving intentions. 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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OpenWhip
Optimize interaction with AI coding assistants
OpenWhip is a desktop utility built as a cross-platform Node.js application that humorously gamifies interaction with AI coding assistants by simulating a “whip” tool to interrupt and motivate them during long or stalled operations. The application runs as a lightweight system tray program and overlays a visual whip animation on the screen when activated, creating an interactive and slightly absurd interface for user engagement. Its core functionality is surprisingly practical beneath the... -
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Future AGI
Open-source platform for evaluating, observing, and improving LLM
Future AGI is an open-source, end-to-end platform for evaluating, observing, protecting, and improving AI agent applications. It is built for teams that need more than basic tracing, combining evaluations, simulations, datasets, guardrails, gateway routing, and optimization in one feedback loop. The platform helps developers detect hallucinations, measure agent quality, monitor production behavior, and use evaluation results to improve prompts or workflows over time. It supports both cloud and self-hosted deployment models, making it useful for teams with different privacy, infrastructure, and compliance needs. Future AGI is especially relevant for agent-heavy products where reliability, regression testing, and safety checks matter before and after release. ... -
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Huashu Design
Huashu Design · HTML-native design skill for Claude Code
...The system is designed to be adaptable, allowing users to customize scripts for different domains or audiences. It also encourages iterative refinement, enabling continuous improvement of conversational strategies based on feedback and performance. The framework can be applied to both human-driven and AI-driven interactions, making it versatile across use cases. Overall, huashu-design offers a systematic approach to crafting and managing effective communication patterns. -
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gpt-engineer
Full stack AI software engineer
...Built with a terminal-based interface, gpt-engineer is customizable, enabling developers to experiment with AI-assisted programming and refine their development process. It is especially useful for automating the coding and iterative feedback loop in software development. -
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AI Engineer Coach
Better agentic engineering
...It is designed to help developers improve how they work with tools such as VS Code, Claude, Codex, OpenCode, GitHub Copilot for Xcode, and Copilot CLI. The extension reads local logs and turns them into dashboards, practice scores, trends, anti-pattern detection, and actionable feedback. It focuses on agentic engineering habits such as prompt quality, context management, review discipline, tool use, and session hygiene. The project is read-only and emphasizes that data stays on the user’s machine. Its main value is helping developers measure and improve their AI-assisted coding process instead of treating agent use as an untracked black box. -
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Skill Scanner
Security Scanner for Agent Skills
This repository is a public security-focused scanning tool intended to analyze and assess AI agent skills for potential issues, quality concerns, and vulnerabilities. It acts as a scanner that inspects Agent Skills packages to flag structural problems, inconsistencies, or security flaws before they are deployed or integrated into agent workflows. Because agent skills can contain executable instructions and logic, scanning them for risky patterns is essential to prevent inadvertent... -
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agent-browser
Browser automation CLI for AI agents
...The project emphasizes standards and safety, defining interfaces that let agents access DOM data, interpret events, and generate actionable insights without exposing sensitive credential-level access or violating policy boundaries. Users benefit from a tighter feedback loop: agents can observe user tasks in-situ and respond with contextually relevant actions or suggested steps, like form completion, navigation shortcuts, or detailed explanations of UI elements. -
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Quark Agent
Quark Agent - Your AI-powered Android APK Analyst
With Quark Agent, you can perform analyses using only natural language. It creates Quark Script code following your ideas and adjusts the code promptly as you provide feedback. -
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Claude Autoresearch
Claude Autoresearch Skill, autonomous goal-directed iteration
Claude Autoresearch is an autonomous research assistant system that automates the process of exploring, collecting, and synthesizing information across multiple iterations. It is designed to mimic human research behavior by generating queries, evaluating results, and refining its approach based on previous findings. The system likely integrates with external data sources, allowing it to gather information from diverse inputs and organize it into structured outputs. Its iterative loop enables... -
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Compound Engineering
Official Compound Engineering plugin for Claude Code, Codex, Cursor
...It also supports automated code review and ideation processes, leveraging multiple agents to enhance quality and decision-making. By codifying patterns and learnings, it creates a feedback loop that improves productivity over time. -
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WrenAI
Open-source SQL AI Agent for Text-to-SQL. Make Text2SQL Easy
Wren AI is a SQL AI Agent for data teams to get results and insights faster by asking business questions without writing SQL, and it's open-source. Wren AI has implemented a semantic engine architecture to provide the LLM context of your business; you can easily establish a logical presentation layer on your data schema that helps LLM learn more about your business context. With Wren AI, you can process metadata, schema, terminology, data relationships, and the logic behind calculations and... -
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SwiftUI Agent Skill
SwiftUI agent skill for Claude Code, Codex, and other AI tools
SwiftUI-Agent-Skill is an advanced agent skill designed to enhance AI coding assistants by embedding expert-level knowledge of SwiftUI development practices into their workflows. It provides structured guidance that helps AI tools generate more accurate, modern, and maintainable SwiftUI code by addressing common mistakes such as misuse of APIs, poor performance patterns, and accessibility oversights. The system includes a comprehensive review process that evaluates code across multiple... -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
...Instead of relying on a single agent, the system allows a leader agent to spawn and coordinate multiple specialized sub-agents, each responsible for different aspects of a problem. These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence. The framework supports a wide range of use cases, including software development, machine learning research, financial analysis, and content production. It is designed to work with various AI tools and command-line agents, making it highly flexible and extensible. ClawTeam also includes monitoring tools such as dashboards and tmux-based views to observe agent activity and progress. -
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MiroThinker
MiroThinker is an open source deep research agent
MiroThinker is an open-source deep research AI agent designed to perform complex reasoning, information gathering, and predictive analysis tasks. The system focuses on enabling long-horizon research workflows by allowing the agent to interact repeatedly with external tools, search systems, and data sources while refining its reasoning through iterative steps. Rather than simply generating responses from a single prompt, the agent performs structured multi-step reasoning processes that...
