ATH-MaaS/ComfyUI-Copilot

An AI-powered custom node for ComfyUI designed to enhance workflow automation and provide intelligent assistance

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Summary Information

Updated 5 minutes ago
Added to GitGenius on September 12th, 2026
Created on February 14th, 2025
Open Issues & Pull Requests: 51 (+0)
GitHub issues: Enabled
Number of forks: 363
Total Stargazers: 5,511 (+0)
Total Subscribers: 65 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 27.2 hours
Mean response time: 4.2 days
90th percentile: 8.8 days
Tracked items: 84

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 6% of issues opened in the past year have been closed. Three people close 87% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 44
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 291 days
Stale 30+ days: 44
Stale 90+ days: 42

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Most active issues this week

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Detailed Description

ComfyUI-Copilot is an AI-powered custom node for ComfyUI that automates workflow building and provides intelligent assistance for image generation development.

The tool addresses the complexity and tedium of constructing ComfyUI workflows by leveraging large language models as agents that understand both the ComfyUI environment and user intent. It operates by analyzing workflow requirements, detecting errors in existing workflows, and generating or rewriting workflows based on user descriptions. The agent architecture is aware of the local ComfyUI setup, allowing it to deliver personalized solutions tailored to available nodes and parameters.

Developers working with ComfyUI who spend significant time debugging workflows, tuning parameters, or building from scratch should consider this tool. It suits projects where rapid iteration and workflow optimization matter, particularly for teams new to ComfyUI who need guidance on node selection and configuration. The tool requires users to provide their own API key and base URL to access agent capabilities, as the hosted service has been suspended. This means adoption depends on having access to a compatible LLM provider.

The project maintains active development across multiple capabilities including one-click workflow debugging, automated workflow rewriting based on user descriptions, and enhanced workflow generation from natural language requirements. The codebase is written in TypeScript and integrates with various LLM providers and image generation models. Community engagement is supported through Discord and WeChat channels, indicating ongoing user interaction and feedback loops.