Generate structured knowledge base updates from paper reading notes.
npx skills add https://github.com/acd19ml/Knowledge-Markdown --skill kb-maintenance
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
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.
Use the kb-maintenance skill to update the knowledge base with the latest reading note.
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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