Search Results for "task" - Page 2
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Showing 40 open source projects for "task"
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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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VT Code
VT Code - semantic AI coding agent
VTCode is a terminal-based AI coding agent designed to provide semantic code understanding and interactive assistance directly within a command-line environment. It is implemented in Rust and focuses on performance, portability, and deep integration with developer workflows that rely on terminal tools. The system leverages syntax-aware parsing technologies such as tree-sitter and AST-based analysis to understand code structure rather than relying solely on raw text, which enables more... -
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HolyClaude
AI coding workstation: Claude Code + web UI + 5 AI CLIs + headless
HolyClaude is a developer-focused toolkit designed to enhance and extend the capabilities of Claude Code environments by providing structured prompts, utilities, and workflow enhancements for AI-assisted coding. The project centers around improving how developers interact with AI agents, enabling more efficient code generation, debugging, and task execution through optimized prompt engineering. It includes predefined templates and interaction patterns that guide the AI toward producing more accurate and context-aware responses. HolyClaude emphasizes productivity by reducing friction in iterative development cycles, allowing users to refine outputs quickly without repeatedly crafting instructions from scratch. ... -
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Claude HUD
A Claude Code plugin that shows what's happening
Claude HUD is a real-time monitoring add-on for Claude Code that places a persistent heads-up display directly in your interactive session, giving developers clear insight into what the AI engine is doing at every moment. Instead of guessing about hidden processes behind the scenes, users see the amount of context remaining in the current session, tools being used, active running agents, and the progress of TODO tasks that the AI has planned or is executing. This plugin was designed to... -
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Claude Cognitive
Persistent context and multi-instance coordination
...It introduces an attention-based context router that prioritizes files and content relevant to the current development discussion — tagging them as HOT, WARM, or COLD based on recency and keyword activation — so Claude Code doesn’t waste token budget rereading irrelevant code. This context routing dramatically reduces redundant token usage and accelerates large codebase interactions by focusing only on what truly matters to the current task. Additionally, Claude-Cognitive includes a pool coordinator to share state across multiple Claude Code instances, preserving what’s been learned or completed and preventing repetitive debugging or redundant exploration. -
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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SmallCode
AI coding agent optimized for small LLMs. 87% benchmark
...It is designed to extract useful coding performance from smaller LLMs, especially models in the 7B to 20B range. The project focuses on making local coding assistance practical without requiring massive cloud-hosted models for every task. Its workflow is built around terminal usage, which makes it suitable for developers who prefer command-line control and local project context. smallcode emphasizes efficient agent behavior, careful tool use, and benchmark-driven improvements for constrained models. Its main value is giving developers a compact coding-agent environment that treats small local models as first-class tools. -
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CoStrict
Strict AI coder for enterprises, quality first
...Unlike typical AI coding tools that prioritize speed over rigor, CoStrict introduces a “strict mode” methodology that enforces disciplined processes such as requirements analysis, architecture planning, task decomposition, and test generation before producing code. This makes it particularly suitable for organizations that require consistency, auditability, and reliability in AI-assisted development. The system integrates repository-wide analysis using retrieval-augmented generation, allowing it to understand large codebases and provide context-aware suggestions, reviews, and modifications. ... -
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.NET Agent Skills
Repository for skills to assist AI coding agents with .NET and C#
...The repository covers core .NET work as well as more specialized areas such as Entity Framework, MSBuild, NuGet, .NET upgrades, .NET MAUI, and AI-related .NET development. Its purpose is to reduce trial and error by giving agents task-specific context and repeatable workflows. The project also includes evaluation and dashboard support to track skill performance over time. It is best suited for developers who use AI coding tools and want better results on real .NET codebases. -
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Mysti
AI coding dream team of agents for VS Code
...Instead of replacing the tools developers already use, it integrates with popular CLI-based coding assistants and routes work through a single, consistent UI inside the editor. The experience is organized around “personas” that change how the assistant approaches a task, such as architecture, debugging, security review, performance tuning, or refactoring, which helps structure the AI’s behavior for different goals. It also supports a brainstorm-style workflow where using more than one backend can produce competing solutions and then synthesize a best answer. Mysti is designed for speed and convenience with quick actions, toolbar persona switching, and a saved conversation history so work is not lost between sessions. -
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Markdown Viewer Agent Skills
Opinionated skills for AI coding agents to create stunning diagrams
Markdown Viewer Agent Skills is a repository that provides a collection of modular AI “skills” designed to extend the capabilities of agents or tools that operate on markdown-based workflows. These skills are typically structured as self-contained instruction sets that define how an AI should perform specific tasks, such as formatting, analysis, or content transformation. The project emphasizes simplicity and composability, allowing developers to integrate these skills into existing systems... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Every Code
Local AI coding agent CLI with multi-agent orchestration tools
Every Code (often referred to simply as Code) is a fast, local AI-powered coding agent designed to run directly in the terminal environment. It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with... -
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Context Hub
Makes coding agents get smarter with every task
Context Hub is a curated documentation system built to help coding agents write more accurate code. It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls,... -
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gpt-engineer
Full stack AI software engineer
gpt-engineer is an open-source platform designed to help developers automate the software development process using natural language. The platform allows users to specify software requirements in plain language, and the AI generates and executes the corresponding code. It can also handle improvements and iterative development, giving users more control over the software they’re building. Built with a terminal-based interface, gpt-engineer is customizable, enabling developers to experiment... -
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Mentat
Mentat - The AI Coding Assistant
Mentat is the AI tool that assists you with any coding task, right from your command line. Unlike Copilot, Mentat coordinates edits across multiple locations and files. And unlike ChatGPT, Mentat already has the context of your project, no copy and pasting is required. Run Mentat from within your project directory. Mentat uses Git, so if your project doesn't already have Git set up, run git init. -
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Aide
The open source AI-native IDE
...Built to act as a full-stack collaborator, it understands multi-file projects, detects dependency relationships, and can generate consistent updates across files and frameworks. It supports multiple backends—including OpenAI, Anthropic, and open-source models—and can route requests based on task type or latency requirements. Aide stores context efficiently, caching embeddings of codebases to accelerate reasoning and maintain memory across sessions. Developers can query Aide for explanations, generate docstrings, fix bugs, or scaffold full modules, all while preserving project structure. With a modular architecture, Aide can run locally for privacy-sensitive work or connect to managed servers for collaborative environments. -
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Kimi K2.7 Code
Coding-focused Kimi model for long-horizon agent workflows
Kimi K2.7 Code is a coding-focused agentic model built on Kimi K2.6, designed for long-horizon software engineering, autonomous coding workflows, and complex tool-based execution. It improves end-to-end task completion across real-world programming scenarios while reducing thinking-token usage by about 30% compared with K2.6. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, 61 layers, 384 experts, a 256K-token context window, and a MoonViT vision encoder. The model supports image and video input, native INT4 quantization, interleaved thinking, and multi-step tool calling. ...
