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jiyangnan
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kb-qa-score

Score normalized knowledge base items on density, verifiability, reusability, clarity, and human touch.

2|Updated Feb 27, 2026
Search Tags:#knowledge management#data analysis#qa automation#quality assessment#kb scoring
One-click install
npx skills add https://github.com/jiyangnan/xiaonangua-openclaw-skills --skill kb-qa-score
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kb-qa-score
Source: https://github.com/jiyangnan/xiaonangua-openclaw-skills/tree/main/KB/kb-skills/kb-qa-score
Command: npx skills add https://github.com/jiyangnan/xiaonangua-openclaw-skills --skill kb-qa-score

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of scoring normalized knowledge base items, determining their value, and deciding their appropriate disposition (keep, discard, queue, needs context).

Core Features & Use Cases

  • Automated Scoring: Uses a predefined scorecard to rate knowledge base items based on information density, verifiability, reusability, clarity, and human touch.
  • Verdict Output: Provides a verdict (keep, discard, queue, needs context) for each item.
  • Use Case: It can be used as part of the workflow in systems that require automated quality assessment of knowledge items, such as in a knowledge base management system.

Quick Start

Run the 'kb-qa-score' skill with the normalized KB item as input.

Frequently Asked Questions about kb-qa-score

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

FAQPage Schema
How can I automate quality assessment for my knowledge base items?▼

Automated quality assessment scores normalized YAML knowledge base items using a predefined scorecard. It evaluates metrics like information density, verifiability, reusability, clarity, and human touch to determine item value.

What is knowledge base scoring and how does it handle content disposition?▼

Knowledge base scoring evaluates the value of normalized items by applying a scoring algorithm. It outputs a specific verdict for each item, deciding its appropriate disposition as keep, discard, queue, or needs context.

How do I evaluate the reusability and clarity of normalized YAML content?▼

To evaluate reusability and clarity of normalized YAML content, run an automated scoring skill. It applies a predefined scorecard to rate these specific metrics alongside information density, verifiability, and human touch.

Does the knowledge base quality assessment require normalized YAML input?▼

Yes, knowledge base quality assessment requires normalized YAML content as input. The scoring algorithm analyzes this specific structured format to evaluate item value and generate keep, discard, queue, or needs context verdicts.

What is the best way to decide which knowledge base items to keep or discard?▼

The best way to decide whether to keep or discard knowledge base items is using an automated scoring algorithm. It rates items on verifiability and reusability, providing a clear disposition verdict for each evaluated entry.

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