Analyze academic texts into structured Markdown summaries with parameterized prompt templates.
npx skills add https://github.com/giraphant/quasi --skill quasi-analyze
Please help me install this Agent Skill. Skill: quasi:analyze Source: https://github.com/giraphant/quasi/tree/main/skills/analyze Command: npx skills add https://github.com/giraphant/quasi --skill quasi-analyze
This Skill automates the in-depth, structured analysis of academic texts like book chapters and research papers, transforming raw content into organized, insightful summaries and analyses.
CLAUDE.md.Analyze the provided paper 'paper.pdf' focusing on the topic 'quantum computing advancements' and save the output to 'quantum_analysis.md'.
High-intent search queries and answers about installing and using this skill.
To analyze a research paper and generate structured markdown output, you process the text using parameterized prompt templates that extract core arguments, theoretical frameworks, and key concept definitions into a formatted report.
Yes, you can extract key concepts and theoretical frameworks from academic book chapters by applying specific analysis templates designed to parse chapter metadata and content into structured summaries.
The best way to summarize academic texts based on a specific research topic is to use parameterized prompt templates that assess relevance against your project-specific topic definitions and analytical stances.
Yes, this academic text analysis approach requires predefined project topics defined in your project preamble to accurately assess the text's relevance and tailor the structured markdown output to your research theme.
Parameterized prompt templates improve knowledge extraction from academic papers by systematically targeting specific analytical dimensions like theoretical contributions and value assessments, ensuring comprehensive and organized markdown documentation.
A limitation when processing single academic texts for structured analysis is that the system focuses on individual documents like book chapters or research papers rather than processing multiple texts simultaneously for cross-document synthesis.
anbeimeDownload arXiv PDFs, extract text, and generate analytical outputs.
AbilityaiClassify information into confirmed findings, theoretical frameworks, hypotheses, and speculative synthesis.
niranjannavExtract text, tables, and metadata from PyMuPDF-compatible PDF documents.
PlagueHOAssess multitenancy documents against the Agent Skills standard and Azure guidance.