skills.rest
agnt-gg
agnt-ggCOMMUNITY
Explore all skills by this author →
Website𝕏@agnt_ggGitHub

pdf-research-corpus-analyzer

Extracts text from PDF collections and generates cross-document concept indexes with sequenced reading plans.

530|67|Updated Mar 13, 2025
Search Tags:#research papers#literature review#PDF#cross-reference#reading plan#pyMuPDF#concept index
One-click install
npx skills add https://github.com/agnt-gg/agnt --skill pdf-research-corpus-analyzer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pdf-research-corpus-analyzer
Source: https://github.com/agnt-gg/agnt/tree/main/backend/skills/pdf-research-corpus-analyzer
Command: npx skills add https://github.com/agnt-gg/agnt --skill pdf-research-corpus-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pymupdf.

What problem does it solve?

Turning a folder of unorganized research PDFs into a coherent understanding is slow and manual. This Skill automates the extraction, cross-referencing, and sequencing work so you get a structured concept index and a page-referenced reading plan instead of a pile of documents.

Core Features & Use Cases

  • PDF Acquisition: Inventory an existing folder of PDFs, or search the web and download 5-10 papers on a given topic from arxiv, ACL Anthology, IEEE, and similar sources.
  • Structured Extraction: Use PyMuPDF to extract per-page text, detect section headings, and map page ranges for every document.
  • Cross-Document Concept Index: Detect 40-60 domain concepts across all papers, invert them into a cross-reference index, and classify concepts into tiers by coverage.
  • Sequenced Reading Plan: Generate a phased reading plan with exact page references, estimated reading times, a 30-minute quick path, and topic deep-dive tables.
  • Use Case: A graduate student with 12 downloaded papers on retrieval-augmented generation runs this Skill to get a concept index showing which ideas appear across papers and a step-by-step reading order with exact pages to read.

Quick Start

Analyze the folder of PDF research papers at my specified path and generate a cross-document concept index with a sequenced reading plan including exact page references.

Frequently Asked Questions about pdf-research-corpus-analyzer

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

FAQPage Schema
How do I analyze a folder of PDF research papers?▼

Point the Skill at your PDF folder and it inventories every file, extracts per-page text with PyMuPDF, detects section headings, and builds a cross-document concept index. The final output is a markdown reading plan with exact page references and estimated reading times.

How to build a reading plan from multiple research papers?▼

The Skill sequences papers by placing surveys before specialized work, foundational concepts before advanced ones, and shorter papers first. Each step in the plan cites exact page ranges and explains why that section comes at that point.

Can I download papers on a topic instead of providing PDFs?▼

Yes. Given a topic, the Skill runs web searches from multiple angles, identifies 5-10 papers from arxiv, ACL Anthology, IEEE, or ACM, downloads them via fetch, and saves them with numbered prefixes before extraction.

Does this use vector embeddings or RAG for document analysis?▼

No. The Skill deliberately avoids embeddings and RAG, using structured text extraction and keyword-based concept indexing instead. This captures argument structure and reading order, which similarity search cannot represent.

What happens with scanned PDFs that have no extractable text?▼

PyMuPDF returns empty pages for scanned documents, so the Skill reports which PDFs failed extraction and suggests OCR alternatives. The rest of the corpus is processed normally.

What are the limitations of keyword-based concept detection?▼

Concept detection is English-focused and depends on a curated keyword list of 40-60 terms tailored to the corpus topic. Non-English content is flagged, and niche concepts outside the keyword list may be missed.

Related Skills

Explore More Education & Research Skills→
sjtuytcsjtuytc
27

arxiv

Search arXiv, download PDFs, extract metadata, and summarize papers.

Community
Advanced
koach08koach08
1

literature-review

Summarize academic PDFs and identify research gaps for literature reviews.

Community
Intermediate
LaZy-WolfLaZy-Wolf
1

academic-paper-agent

Searches arXiv by keyword and extracts metadata for academic papers and citations.

Community
Intermediate
zilliztechzilliztech
3

semantic-search

Convert text into embeddings and retrieve semantically similar items from a vector store.

Official
Intermediate