I built the first AI-agent-friendly Amazon catalog tool. Here's why. As an Amazo
By Brett Bohannon · February 25, 2026 · Curated by George's Blog
I built the first AI-agent-friendly Amazon catalog tool. Here's why.
As an Amazon consultant, I spend hours manually auditing Category Listing Reports (CLRs) for clients. Missing attributes, RUFUS optimization, title validation—it's tedious, repetitive work that should be automated.
So I built a tool that does it in seconds.
Introducing: Amazon Catalog CLI
A free, open-source command-line tool designed for:
• Amazon consultants automating catalog audits
• Agencies managing multiple seller accounts
• AI agents that need structured catalog data
What it does:
✅ 9 built-in catalog health checks (more to come)
✅ RUFUS bullet point scoring (Amazon's AI shopping assistant framework) - more to come on this as well
✅ Missing attribute detection (required + conditional fields)
✅ Title validation, character checks, product type matching
✅ JSON/CSV export for automation and AI workflows
Why "agent-native"?
Most tools are built for humans clicking buttons. This is built for AI agents and scripts. Structured output, CLI interface, easy integration.
Example use case: An AI agent audits a CLR, identifies 47 issues across 23 SKUs, and generates a prioritized action plan—all automatically.
It's free and open source (MIT license).
Two ways to use it:
1. Standalone CLI:
```
pip install amazon-catalog-cli
```
2. OpenClaw Skill:
Download from https://lnkd.in/g8TJ2YDh
Natural language: "Audit this CLR and tell me what to fix"
CLI: https://lnkd.in/gDfGJRSp
PyPI: https://lnkd.in/gckYc-2x
OpenClaw Skill: https://lnkd.in/g8TJ2YDh
Looking for feedback:
If you work with Amazon catalogs, I'd love to hear what queries/checks would be most useful. Contributions welcome.