skylos vs MaxKB
skylos: Skylos is a privacy-first, hybrid static analysis tool designed for Python, TypeScript, and Go. It excels at detecting dead code, critical security vulnerabilities like SQL injection and hardcoded secrets, and various code quality issues, bridging traditional static analysis with advanced AI agent capabilities.; MaxKB: MaxKB is an open-source platform for building enterprise-grade AI agents with integrated RAG pipelines, workflow orchestration, and MCP tool-use capabilities. It supports direct document upload, automatic web crawling, and multiple embedding models for knowledge base construction. Widely used for intelligent customer service, internal knowledge bases, and academic research applications.
TL;DR
Automating Code Quality in CI/CD: Integrate Skylos into GitHub Actions to automatically detect dead code, security vulnerabilities, and quality issues on every Pull Request, failing builds on critical findings.
- You want an all-in-one knowledge-base and workflow agent platform that starts with a single Docker command and embeds easily into websites.
- You need broad support for domestic Chinese LLM providers alongside global models for internal enterprise Q&A.
- You cannot use GPL-3.0 licensed software in your commercial distribution; RAGFlow is Apache-2.0.
- Your primary bottleneck is extracting complex tables and layouts from messy scanned PDFs; RAGFlow's deep document parser goes further.
Side-by-Side Comparison
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