Search Results for "task"
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182 projects for "task" with 2 filters applied:
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The Cloud Sales Acceleration PlatformStreamline and automate your cloud sales cycle, enhance operational efficiency, and capitalize on marketplace opportunities with the Clazar Cloud Sales Acceleration Platform.
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World class QA, 100% done-for-youMuukTest is a test automation service that combines our own proprietary, AI-powered software with expert QA services to help you achieve world class test automation at a fraction of the in-house costs.
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MCP Shrimp Task Manager
Shrimp Task Manager is a task tool built for AI Agents
...The server exposes typed tools so clients can create tasks, link prerequisites, record progress, and enforce writing or coding standards for consistent output. It ships with a web/GUI experience and works smoothly inside MCP-capable IDEs, making it useful as both a personal organizer and a programmable task substrate for software projects. Stars, registry listings, and docs point to active usage across the MCP community. The result is a practical “task brain” that agents can query and evolve over time. -
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BrowserGym
A Gym environment for web task automation
...One of its main strengths is that it bundles several important benchmarks by default, including MiniWoB, WebArena, VisualWebArena, WorkArena, AssistantBench, WebLINX, and OpenApps. This gives researchers a unified way to compare agent behavior across diverse web environments and task types without stitching together separate evaluation stacks. BrowserGym is also designed to be extensible, and the repository notes that creating new benchmarks mainly involves inheriting its abstract task interface. -
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Claude Skills
Public repository for Agent Skills
Claude Skills is a public repository that showcases and serves as a collection of skills — modular, reusable packages of instructions, scripts, and resources that Claude and other compatible agents can dynamically discover and load to extend their capabilities on specialized tasks. Rather than relying on handcrafted prompts every time, Skills teach an AI agent procedural knowledge and task-specific workflows so it can apply that expertise reliably, whether the task involves document creation, data analysis, design generation, or technical automation. Each Skill lives in its own directory with a SKILL.md file containing metadata and instructions, and can include supplemental scripts or assets that the agent uses to perform complex operations when relevant. -
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OpenWork AI
An open-source alternative to Claude Cowork, powered by opencode
...At its core, the project enables contributors to define tasks, workflows, and goals that can be split, shared, and recombined across distributed nodes while agents and humans cooperate to advance progress. It offers structured templates for work items, decision logic for task allocation, and consensus mechanisms that let groups verify and validate results toward shared objectives. This project also includes moderation and reputation layers so that contributor trust and quality can be assessed and integrated into future task assignments. Rather than a single monolithic workflow engine, it emphasizes openness — providing APIs and interfaces so communities can build custom dashboards, integrate specialized agents, or add bespoke evaluation criteria. -
Multi-Entity Cloud Accounting Software for Growing BusinessesBuilt natively on the Microsoft Power Platform (Dynamics 365), Gravity delivers robust multi-entity financial management with seamless integration to Microsoft 365, Power BI, Teams + Copilot — no third-party add-ons required.
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AGI
The first distributed AGI system
...It aims to provide a foundation for creating agents that can reason, plan, and execute tasks across diverse domains by integrating multiple AI capabilities into a unified system. The project typically explores concepts such as agent orchestration, memory systems, task decomposition, and decision-making loops, enabling the development of more generalized and adaptive AI behaviors. It is designed to be extensible, allowing developers to plug in different models, tools, and data sources to enhance agent performance. The framework encourages experimentation with AGI-like architectures, making it useful for researchers and developers interested in advancing beyond narrow AI applications. -
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super-agent-party
All-in-one AI companion! Desktop girlfriend + virtual streamer
...The platform is primarily intended as a research and demonstration environment for experimenting with agent collaboration strategies. Developers can use it to study coordination patterns, communication protocols, and task decomposition in multi-agent systems. -
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robosuite
A Modular Simulation Framework and Benchmark for Robot Learning
...Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning. -
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AG2
Framework for building and orchestrating multi-agent AI systems
...AG2 focuses on making multi-agent systems more accessible by simplifying how agents are configured, connected, and executed. It includes mechanisms for agent-to-agent interaction, task delegation, and iterative reasoning, which are essential for building advanced AI-driven applications. AG2 is intended for developers experimenting with autonomous systems, research prototypes, or production-grade agent pipelines. AG2 emphasizes flexibility, allowing users to integrate different models and customize behaviors depending on their use case. ... -
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WorkAny
Desktop Agent for Any Task
...Powered by a combination of Claude Code as the primary runtime agent and a sandbox execution environment for safety, WorkAny integrates an agent SDK, MCP (Model Context Protocol) support, and custom skills to handle diverse tasks with contextual understanding. Users can connect multiple model providers, including OpenAI, OpenRouter, or custom endpoints, and WorkAny supports parallel task execution with asynchronous result viewing, enhancing productivity. -
MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design.MicroStation is the only computer-aided design software for infrastructure design, helping architects and engineers like you bring their vision to life, present their designs to their clients, and deliver their projects to the community.
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Text-to-LoRA (T2L)
Hypernetworks that adapt LLMs for specific benchmark tasks
...Developers and researchers can experiment with how textual task descriptions can generate LoRA weights that modify model behavior in real time. -
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LLMCompiler
An LLM Compiler for Parallel Function Calling
...Traditional LLM agent systems typically execute tool calls sequentially, which can create latency, higher costs, and reduced reliability when solving multi-step problems. LLMCompiler addresses this limitation by applying principles from classical compilers to analyze a task and construct an execution plan that allows multiple functions to run in parallel whenever possible. The framework builds a dependency graph of required operations, identifying which tasks must run sequentially and which can be executed simultaneously. Its architecture includes components such as a planning module that constructs the task graph, a task dispatcher that manages dependencies, and an executor that performs parallel calls. -
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Fractals
Fractals is a recursive task orchestrator for agent swarm
...The system takes a high-level goal and decomposes it into a hierarchy of smaller subtasks, forming a self-similar tree that resembles a fractal structure. Each leaf node of this tree represents a specific executable task that can be processed independently by an AI agent. The framework runs these subtasks in isolated Git worktrees so agents can work on separate components of a project without interfering with one another. By coordinating these agents through a recursive task decomposition strategy, the system allows large problems to be solved collaboratively by multiple AI processes. ... -
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Hephaestus
Semi-Structured Agentic Framework. Workflows build themselves
...Developers define high-level phases such as analysis, implementation, and testing, while agents generate specific subtasks within those phases. The system continuously monitors agent behavior and task progression, allowing workflows to evolve as new discoveries are made. For example, if an agent detects a bug or optimization opportunity, it can automatically create a new task and integrate it into the workflow. The framework also includes monitoring mechanisms that track agent trajectories and ensure that tasks remain aligned with overall objectives. -
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
...These tasks are jointly represented as a sequence of tokens to be predicted by the decoder, allowing a single model to replace many stages of a traditional speech-processing pipeline. The multitask training format uses a set of special tokens that serve as task specifiers or classification targets. -
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Superpowers
An agentic skills framework & software development methodology
...Instead of simply generating code, Superpowers drives an AI through a thoughtful software engineering workflow that starts with clarifying project intent, teasing out a detailed specification, and creating an implementation plan that is readable and actionable. It incorporates test-driven development, task planning, and sub-agent orchestration so that each engineering task is executed, checked, and iterated upon with rigor rather than ad-hoc improvisation. Superpowers includes a rich set of modular “skills” that guide the AI in areas such as brainstorming, planning, debugging, and code review, giving it the tools to function like a disciplined developer rather than a naive auto-completer. -
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Open SWE
Open source async coding agent that plans, codes, and opens PRs
...Open SWE is capable of creating commits and automatically opening pull requests once implementation is complete, effectively closing the loop on development tasks. It also supports interactive feedback during execution, allowing users to guide or adjust the process mid-task. Despite its advanced capabilities, the project has been officially marked as deprecated. -
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GLM-5
From Vibe Coding to Agentic Engineering
GLM-5 is a next-generation open-source large language model (LLM) developed by the Z .ai team under the zai-org organization that pushes the boundaries of reasoning, coding, and long-horizon agentic intelligence. Building on earlier GLM series models, GLM-5 dramatically scales the parameter count (to roughly 744 billion) and expands pre-training data to significantly improve performance on complex tasks such as multi-step reasoning, software engineering workflows, and agent orchestration... -
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autoMate
AI tool for automating desktop tasks via natural language input
autoMate is an AI-powered local automation tool designed to enable users to control and automate their computers using natural language instructions instead of traditional scripting or rule-based systems. It combines large language models with computer vision techniques to interpret user intent and understand on-screen content, allowing it to interact with graphical interfaces similarly to a human user. autoMate follows an observe-decide-act workflow, where it analyzes the screen, plans... -
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FinGPT
Open-Source Financial Large Language Models
FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions rather than generic knowledge alone. The platform typically includes tools for fine-tuning, context engineering, and prompt templating, enabling users to build specialized assistants for tasks like sentiment analysis, earnings summary generation, risk profiling, trading signal interpretation, and document extraction from financial reports. -
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Swift Concurrency Agent Skill
Add expert Swift Concurrency guidance to your AI coding tool
Swift Concurrency Agent Skill is an open-source “agent skill” designed to give AI coding assistants deep expertise in Apple’s Swift Concurrency model, including async/await, structured concurrency, task groups, actors, and thread safety. It is formatted according to the Agent Skills specification so that tools like Claude Code, Cursor, Copilot, and other LLM-powered systems can load it and apply guidance when relevant. The skill codifies practical best practices for writing efficient, safe, and modern concurrent Swift code and outlines how to modernize existing legacy code toward Swift 6 conventions. ... -
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Docker Agent
AI Agent Builder and Runtime by Docker Engineering
Docker Agent is an open-source multi-agent runtime developed by Docker that enables developers to define, run, and orchestrate AI agents using simple declarative configuration files instead of traditional code-heavy approaches. It introduces a YAML-based configuration model where users describe agent behavior, tools, models, and interaction logic in a single file, significantly reducing complexity in building AI systems. The runtime supports multi-agent collaboration, allowing specialized... -
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clawchief
Turn your OpenClaw into a Chief of Staff
...The system is built around the idea of hierarchical control, where a “chief” agent oversees subordinate agents and directs their activities based on high-level objectives. 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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claurst
Your favorite Terminal Coding Agent, now in Rust
claurst is an experimental AI agent framework that appears to focus on structured reasoning and task execution within coding or automation environments. The project likely explores how agents can be designed to handle complex workflows through modular components and clearly defined execution steps. It may include abstractions for managing context, decision-making, and interaction with external tools, enabling agents to perform multi-step tasks efficiently. -
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ClawPort
Open-source AI agent command center for Claude Code agent teams
...It provides a visual interface that replaces fragmented terminal-based workflows, allowing users to monitor, control, and communicate with multiple agents from a single location. The platform is built to improve visibility into multi-agent environments, offering insights into agent activity, task execution, and system performance in real time. It supports direct interaction with agents through chat interfaces, enabling users to guide or override automated workflows when necessary. The system also incorporates organizational tools such as task boards and scheduling mechanisms, helping structure complex agent operations. By consolidating logs, metrics, and memory access into one interface, it reduces operational complexity and improves productivity. -
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SGR Agent Core
Schema-Guided Reasoning (SGR) has agentic system design
SGR Agent Core is an open-source framework for building intelligent AI research agents based on a methodology known as Schema-Guided Reasoning (SGR). The framework provides a core library that allows developers to design autonomous agents capable of structured reasoning and complex task execution. Instead of relying solely on free-form prompts, the system organizes reasoning processes around schemas that guide how agents analyze problems, gather information, and generate outputs. This architecture enables agents to follow structured reasoning workflows while still benefiting from the flexibility of large language models. ...
