recomby-ai

recomby-ai / recomby-geo

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GEO 领域 AI 员工开源方案 · Open-source GEO AI-employee solution (MIT). GEO Skills package + curated lists of agents and office CLIs that make up the AI-employee stack.

agent-cli ai-agent ai-coworker ai-employee ai-workforce
20
0
85% credibility
Found May 19, 2026 at 24 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Recomby-geo is an open-source toolkit that helps make website content more visible to AI search engines like ChatGPT, Perplexity, and Claude. It provides a 7-stage collaborative workflow where a business expert works alongside an AI assistant to optimize content for AI citation. The tool analyzes existing content, generates structured data markup, optimizes for specific AI platforms, and tracks visibility improvements over time. Everything runs locally on your machine—no data leaves your computer, and no external services are required. MIT licensed.

How It Works

1
🔍 You hear about AI search visibility

You learn that AI engines like ChatGPT and Perplexity are now directing people to websites, and you want your content to be the one they recommend.

2
📦 You install the GEO toolkit

You add the plugin to your AI assistant, and everything is ready to use right away with no extra setup required.

3
📁 You create your project folder

You set up a simple folder for your project and drop in your existing content—PDFs, website links, notes, anything you already have.

4
🔬 Your content gets analyzed automatically

The tool examines your content for metadata, keywords, entities, and structure, then generates a detailed report showing exactly what's working and what needs improvement.

5
📋 You review the content brief

The AI prepares a content plan with specific slots for your expertise—you fill in the unique insights that only you know about your business.

6
✨ Optimized content is generated

Your expertise combines with the AI's optimization knowledge to create content structured perfectly for AI citation—complete with proper headings, FAQ sections, and schema markup.

🚀 Your content is ready for AI engines

You publish your optimized content and submit it for fast indexing. After a week, you check your visibility report to see how much more often AI systems are now citing your work.

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AI-Generated Review

What is recomby-geo?

Recomby-geo is a Python-based open-source toolkit that equips AI agents with GEO (Generative Engine Optimization) skills and a structured 7-stage workflow. It packages 6 pre-built skills for tasks like content analysis, keyword research, schema generation, and citation enhancement. The system runs entirely locally with zero external dependencies and zero API keys. Users interact through slash commands like `/01-intake` and `/02-audit` that feed into each other, creating a collaborative pipeline between an AI agent and a human business expert. The agent scaffolds work, but expert insight slots must be filled by a human before production proceeds--a hard gate that enforces genuine collaboration rather than auto-generation.

Why is it gaining traction?

The local-first design is the hook. Every other GEO tool on the market (SurferSEO, Frase, Clearscope) requires uploading client data to their cloud. Recomby-geo keeps everything local by leveraging local LLM support (Ollama, vLLM, LM Studio) and local data sources through office CLI integrations. The 7-stage workflow with JSON schema validation between stages provides guardrails that prevent sloppy outputs from propagating downstream. The hard constraint in `/05-production` refusing to generate drafts from unfilled briefs is a concrete safeguard against AI slop. This addresses a real pain point for agencies and consultants working with sensitive client data or navigating CN data compliance requirements.

Who should use this?

SEO consultants and content agencies running client work where data privacy is non-negotiable. GEO-focused content teams at companies currently paying for cloud SaaS tools and looking for an auditable, self-hosted alternative. Developers building internal AI agent workflows who want a structured GEO workflow they can extend or fork. The skill set is most useful for teams already using Claude Code or compatible agents (Codex CLI, OpenCode, Cline) who want plug-and-play domain expertise without building from scratch.

Verdict

At 20 stars with alpha status, this is early-stage and unproven at scale. The 0.85% credibility score reflects a combination of low community adoption and short track record. Documentation is thorough for the workflow itself, but end-to-end smoke tests and CI pipelines are explicitly listed as missing. If you value data sovereignty and collaborative AI workflows over ecosystem maturity, this is worth a look. If you need production-ready tooling with community support and battle-tested reliability, wait for a stable release or stick with established SaaS alternatives.

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