kb-maintenance

Generate structured knowledge base updates from paper reading notes.

Updated Feb 28, 2026

Search Tags:#automation #research #knowledge base #paper analysis #gap tracking #comparison matrix

Ready to run

npx skills add https://github.com/acd19ml/Knowledge-Markdown --skill kb-maintenance

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kb-maintenance
Source: https://github.com/acd19ml/Knowledge-Markdown/tree/main/Skills/kb-maintenance
Command: npx skills add https://github.com/acd19ml/Knowledge-Markdown --skill kb-maintenance

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the process of updating a research knowledge base by extracting key information from newly read papers and structuring it for comparison matrices and gap trackers.

Core Features & Use Cases

Automated Knowledge Base Updates: Generates structured updates for comparison matrices and gap trackers based on paper reading notes.
Evidence Traceability: Ensures all updates are linked back to specific evidence in the original papers.
Use Case: After finishing a paper on agent memory, use this skill to automatically create a new entry in your comparison matrix detailing the system's memory type and persistence, and to update any relevant gaps in your research tracker with new evidence or limitations.

Quick Start

Use the kb-maintenance skill to update the knowledge base with the latest reading note.

Frequently Asked Questions about kb-maintenance

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

FAQPage Schema

How do I automatically update a research knowledge base from paper reading notes?▼

Updating a research knowledge base from reading notes involves extracting system details, memory mechanisms, and benchmark results to generate structured entries for comparison matrices and gap trackers.

What is a comparison matrix in paper analysis and how does it work?▼

A comparison matrix in paper analysis organizes extracted system details, memory mechanisms, and benchmark results into structured rows, ensuring every entry maintains evidence traceability with direct citations from the original papers.

How do I track research gaps from newly read academic papers?▼

Tracking research gaps from newly read academic papers requires identifying new evidence, limitations, and counter-evidence within the reading notes, then appending those findings to a gap tracker file with linked citations for traceability.

Can I use this skill to extract self-evolution capabilities from agent memory papers?▼

Yes, you can use this skill to extract self-evolution capabilities and memory persistence details from agent memory papers, directly structuring that information into dedicated comparison matrix columns for your knowledge base.

What is the best way to maintain evidence traceability in a research knowledge base?▼

Maintaining evidence traceability in a research knowledge base is achieved by linking every structured update for comparison matrices and gap trackers directly to specific evidence and citations within the original paper reading notes.