Search Results for "planning"
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Showing 10 open source projects for "planning"
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1
Kun
AI agent workspace with Code and Write modes built into your apps
...It is useful for users who want an AI coding environment that treats planning, documentation, implementation, and acceptance review as one continuous workflow. -
2
Compound Engineering
Official Compound Engineering plugin for Claude Code, Codex, Cursor
The Compound Engineering plugin project is an AI-driven workflow system designed to improve software development by turning each unit of work into a reusable and compounding asset. It provides a structured set of commands and agents that guide developers through stages such as brainstorming, planning, execution, review, and knowledge capture. The core philosophy is to reduce technical debt by emphasizing thorough planning and continuous learning, ensuring that each iteration improves future work rather than increasing complexity. The plugin integrates with multiple AI coding environments, including Claude Code and other tools, enabling consistent workflows across platforms. ... -
3
Mercury Agent
Soul-driven AI agent with permission-hardened tools, token budgets
Mercury Agent is a framework for building autonomous AI agents capable of executing complex workflows with minimal human intervention. 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. ... -
4
LazyCodex
The one and only agent harness for complex codebases
LazyCodex is an agent harness for using Codex on complex software projects. It is designed to add structure around AI coding sessions through memory, planning, execution, verification, skills, hooks, routing, and diagnostics. The project helps developers move beyond one-off prompts by giving the agent a more organized workflow inside a codebase. 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. ... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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5
Poco Claw
A more beautiful and easier-to-use alternative to OpenClaw
...The system operates on a sandboxed runtime, ensuring that tasks executed by the agent are isolated from the host environment, which improves security and reliability. It extends beyond simple chatbot functionality by supporting structured workflows, task planning modes, and multi-step execution pipelines. The platform also allows users to manage files and contexts directly within the interface, enabling more complex interactions with data and projects. It is built to make AI agent systems accessible to a broader audience, including users who may not be comfortable with command-line environments. -
6
Dexter
An autonomous agent for deep financial research
Dexter is an autonomous agent tailored for deep financial research: you pose complex financial questions (for example, about a company’s revenue growth or financial ratios) and Dexter breaks them down into structured research tasks, fetches relevant real-time data (e.g. income statements, cash flows), performs analysis, and returns data-backed answers. It uses a multi-agent architecture with components such as a planning agent (to decompose queries), an action agent (to run tasks & fetch data), and self-validation mechanisms: after getting results, Dexter checks its own outputs and refines them until it is confident about its answer. This means it's more than a simple script — it’s a research assistant that loops through analysis steps until convergence. -
7
infinite-canvas
Infinite Canvas Workbench for AI creation integrates AI generation
infinite-canvas is an open-source visual workspace for AI-assisted image creation and iterative creative planning. It combines canvas organization, image generation, reference image editing, chat assistance, prompt libraries, and asset management in one interface. Users can work across multiple canvases, drag and scale nodes, connect ideas visually, use a minimap, undo changes, and import or export work. The project supports OpenAI-compatible API connections for text-to-image, image-to-image, reference editing, text chat, audio generation, and video generation. ... -
8
Open Multi-Agent
One runTeam() call from goal to result
Open Multi-Agent is a flexible framework designed to enable the creation and coordination of multiple AI agents working together to solve complex tasks through collaboration. It focuses on distributing responsibilities across specialized agents, each handling a specific part of a problem, such as planning, execution, or validation. The system emphasizes modularity, allowing developers to define agent roles, communication protocols, and workflows. It supports iterative collaboration, where agents exchange information and refine outputs collectively. The architecture is designed to be extensible, enabling integration with external tools and APIs to expand agent capabilities. ... -
9
oh-my-claudecode
Teams-first Multi-agent orchestration for Claude Code
...The project abstracts away the complexity of interacting with multiple AI agents by introducing a “team-based” execution model, where tasks are automatically decomposed into planning, execution, verification, and iteration stages. It emphasizes natural language interaction, allowing developers to describe goals instead of memorizing commands or manually orchestrating workflows. The system integrates multiple AI providers and tools, enabling parallel execution and cross-validation of tasks across different models. ... -
Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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10
Kanwas
Shared context board for teams and agents
...It is designed for long-running projects where maintaining context matters as much as producing a single response. Overall, Kanwas positions itself as a multiplayer thinking space for AI-assisted research, planning, and execution.
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