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Showing 12 open source projects for "error"
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1
SkillKit
Supercharge AI coding agents with portable skills
...It supports integration with common agent runtimes and toolkits, allowing skills to be plugged into existing architectures without requiring deep infrastructure rewrites. The kit also includes example skills, documentation on best practices, and mechanisms for handling edge cases such as error states, fallbacks, and contextual switches. -
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ComfyUI-Copilot
AI assistant for ComfyUI workflow generation, debugging, and tuning
...ComfyUI-Copilot leverages large language model capabilities to analyze user intent, recommend nodes, and suggest models that match specific requirements. It also provides automated error detection and repair suggestions, improving reliability during development. -
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MCPJam
Postman for MCPs - A tool for testing and debugging MCPs
Inspector by MCPJam is a visual developer tool—akin to Postman—for testing and debugging MCP servers, with capabilities to simulate and trace tool execution via various transports and LLM integrations. -
4
Happy Coder
Mobile and Web client for Codex and Claude Code, with realtime voice
Happy is an open-source, cross-platform mobile and web client designed to bring powerful AI coding agents such as Claude Code and Codex to your fingertips no matter where you are. At its core, Happy wraps existing AI coding tools with a unified interface, providing real-time voice interactions, encrypted communication, and seamless device switching between desktop and mobile. You can start a coding session locally through the Happy CLI or connect from a phone or browser, allowing developers... -
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5
LiteParse
A fast, helpful, and open-source document parser
...LiteParse supports integration with multiple language models, allowing developers to choose the best balance between accuracy and efficiency. It also includes mechanisms for validation and error handling, ensuring that outputs conform to expected schemas and reducing the need for manual postprocessing. The library is particularly useful for tasks such as data extraction, document processing, and building pipelines that require structured outputs from natural language input. -
6
Zypher Agent
A minimal yet powerful framework for creating AI agents
...Zypher prioritizes native support for multiple model providers such as OpenAI and Anthropic Claude, while also offering a rich set of tools for file system operations, search, and terminal execution. It includes mechanisms like checkpointing to version agent decision states, concurrency protections, error handling, and operational interceptors to customize behavior after each reasoning step. Its API is built with TypeScript and is suitable for production contexts where agents must handle real tasks with configurability, logging, and observability. -
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n8n-MCP
A MCP for Claude Desktop / Claude Code / Windsurf / Cursor
...It ships with organized resources and tool definitions that map cleanly to n8n’s ecosystem, improving reliability compared with ad-hoc prompt patterns. The project targets practical agent ops: safer mutations, better error reporting, and predictable behavior when automating or refactoring automations. Community posts highlight the goal of giving agents accurate knowledge of hundreds of n8n nodes and keeping that knowledge fresh as n8n evolves. -
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PearAI
The Open Source AI-Powered Code Editor. A fork of VSCode and Continue
...This also works with choosing specific folders, online docs, terminal content, files, and more. PearAI can directly code in your files, and allow you to see diffs. Try CMD+I (CTRL+I on Windows). Here, we ask PearAI to help us add error handling and comments. Without writing a single line of code, we were able to make a new feature in an unfamiliar codebase: adding a documentation page to the PearAI landing page. Speed up your development process by seamlessly integrating AI into your workflow. PearAI's goal is to reduce the time it takes for an individual to go from idea to creation. ... -
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Super Magic
All-in-one AI productivity platform with agents, workflows, and IM
...It is not a single tool but a complete product ecosystem composed of multiple integrated systems that work together to enhance productivity across different business scenarios. Magic centers around a general-purpose AI agent system called Super Magic, which can autonomously understand tasks, plan actions, execute workflows, and perform error correction. Alongside this, Magic includes a visual workflow engine that enables users to design complex AI processes using a drag-and-drop interface without requiring extensive coding knowledge. It also provides an enterprise-grade instant messaging system that integrates AI conversations with internal communication, allowing teams to collaborate while leveraging intelligent assistants. ... -
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10
FlowGram
Extensible workflow development framework
FlowGram is an open-source, node-based workflow development framework and toolkit aimed at helping developers build custom AI-workflow platforms or automation systems through a visual, drag-and-drop interface. Instead of shipping as a ready-made product, it provides the building blocks — a canvas for wiring together nodes, a form engine for configuring node parameters, a variable-scope and type-inference engine, and a set of “materials” (pre-built node types such as code execution,... -
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Ralph AI Agent
AI agent loop that runs repeatedly until all PRD items are complete
...Designed for extensibility, the framework supports multi-model providers so agents can switch between models or fall back based on task needs. It also aims to be practical for production by including logging, error handling, and state persistence so that agents can resume interrupted workflows. -
12
ModelFusion
The TypeScript library for building AI applications
...The library supports a wide range of model types, including text generation models, vision models, text-to-speech engines, speech-to-text systems, and embedding models. It also includes built-in production features such as observability hooks, logging, automatic retries, and error handling mechanisms that improve reliability when deploying AI systems in real-world environments.
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