kb-normalize

Convert fetched content into standardized YAML with source URL, summary, claim, and evidence.

2|Updated Feb 27, 2026

Search Tags:#knowledge base #YAML #data organization #content normalization #structured information

Ready to run

npx skills add https://github.com/jiyangnan/xiaonangua-openclaw-skills --skill kb-normalize

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kb-normalize
Source: https://github.com/jiyangnan/xiaonangua-openclaw-skills/tree/main/KB/kb-skills/kb-normalize
Command: npx skills add https://github.com/jiyangnan/xiaonangua-openclaw-skills --skill kb-normalize

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the challenge of converting diverse content sources into a standardized YAML format, facilitating easier processing and analysis by downstream systems.

Core Features & Use Cases

Content Normalization: Converts fetched content into a structured YAML format suitable for knowledge base management.
Use Case: Ideal for automating the organization of research findings, articles, and other content into a consistent format for further analysis or storage.

Quick Start

Normalize the content from the URL 'https://example.com/article' using the 'kb-normalize' skill.

Frequently Asked Questions about kb-normalize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I convert fetched web content into a structured YAML format?▼

To convert fetched web content into a structured YAML format, you can use a content normalization script that extracts source URL, summary, claim, and evidence, organizing the information into KB canonical YAML.

What is the best way to normalize research findings for a knowledge base?▼

Normalizing research findings for a knowledge base involves standardizing diverse content sources into a consistent YAML schema. This process extracts and structures key information, facilitating easier downstream processing and analysis.

Can I use Python to organize extracted article claims and evidence into YAML?▼

Yes, you can use Python for data processing to organize extracted article claims and evidence into YAML. Python scripts can parse fetched content from various sources and output standardized structured information.

Does kb-normalize work with content fetched from any URL?▼

Yes, kb-normalize processes fetched content from various sources including specific URLs. It extracts the source URL, summary, claim, and evidence, converting the fetched text into a standardized YAML output format.

When do I need content normalization for structured information?▼

You need content normalization for structured information when you have diverse content sources that must be converted into a standardized YAML format. This is ideal for automating the organization of research findings for knowledge base management.