Individual skill
research-paper-kb
Build a persistent cross-session knowledge base from academic papers
skills/research/methodology/research-paper-kb/SKILL.md
Source commit bf44b3cd617fa94c8a1b254c5d1987142ca3d631
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 5, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 312
- Repository last updated
- Jun 19, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- research Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Read excerpt
# Research Paper Knowledge Base
Build and maintain a persistent, structured knowledge base from academic papers that persists across sessions. This skill enables cumulative literature understanding by storing extracted insights, cross-references, and analytical notes in a queryable format that grows with each reading session.
## Overview
A core challenge in literature review work is that insights from individual papers are often lost between reading sessions. Researchers read a paper, extract key findings, then move on -- only to forget critical details weeks later when writing their own manuscript or encountering a related paper. Traditional reference managers store metadata and PDFs but do not capture the analytical work of reading: the connections between papers, the critiques of methodology, the synthesis of findings across studies.
This skill creates a structured knowledge base that captures not just what papers say, but how they relate to each other and to the researcher's own questions. Each paper entry includes standard metadata, section-by-section notes, methodological assessments, extracted claims with evidence quality ratings, and explicit connections to other papers in the knowledge base.
The knowledge base is stored in a human-readable format (Markdown + YAML frontmatter) that can be version-controlled with git, searched with standard tools, and read by both humans and AI assistants. When returning to the literature after days or weeks, the researcher (or their AI assistant) can query the knowledge base to recall prior findings, identify gaps, and build on accumulated understanding.
## Knowledge Base Structure