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paper-wiki

Initialize Markdown paper vaults, generate canonical indexes, and produce evidence-validated survey reports.

76|1|Updated Apr 22, 2026
Search Tags:#literature review#academic knowledge base#evidence-validated reporting#journal recommendation#multi-dimensional tagging#arxiv web supplementation
One-click install
npx skills add https://github.com/moonlarry/awesome-llm-paper-wiki --skill paper-wiki
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-wiki
Source: https://github.com/moonlarry/awesome-llm-paper-wiki/tree/main/paper-wiki
Command: npx skills add https://github.com/moonlarry/awesome-llm-paper-wiki --skill paper-wiki

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires argparse, gzip, html.parser, io, json, os, re, ssl, subprocess, sys, tarfile, time, urllib.parse, urllib.request, xml.etree.ElementTree, pathlib, hashlib, dataclasses, datetime, typing, and includes scripts (resource) and references (resource) components.

What problem does it solve?

paper-wiki solves the problem of turning a growing local collection of academic paper Markdown files into a structured, searchable, and continuously evolvable literature knowledge base that can produce survey reports and submission recommendations.

Core Features & Use Cases

  • Vault initialization and organization: initialize the vault structure and organize papers into paper/{direction}/{journal_abbr}/ journal buckets.
  • Canonical indexing + multi-dimensional tagging: ingest source papers to generate canonical index pages and assign structured tags (task, method, dataset, domain, signal, application, metric, custom).
  • Full survey generation with evidence controls: generate journal reports, direction reports, stats, direction reviews, and idea discovery/novelty checks, with mandatory evidence-validation gating for coverage-complete reports.
  • Submission and revision guidance: recommend target venues and generate revision suggestions based on canonical metadata.
  • Web supplementation: query OpenAlex, Semantic Scholar, and arXiv, and optionally fetch arXiv full text to enrich the vault.

Quick Start

Tell your agent: Initialize a paper vault at ~/Documents/my-papers, then Scan papers and generate a journal report for your target journal.

Frequently Asked Questions about paper-wiki

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

FAQPage Schema
How do I create a structured literature review from local Markdown paper files?▼

To create a structured literature review, initialize a paper vault to organize local Markdown paper files into journal buckets, generate a canonical index, and assign multi-dimensional tags for searchable academic knowledge base generation.

What is evidence-validated reporting for academic surveys?▼

Evidence-validated reporting enforces mandatory completeness gates before generating journal or direction reports, ensuring academic survey output is fully backed by canonical metadata extracted from ingested source papers.

Can I enrich my local paper vault with web supplementation from arXiv and OpenAlex?▼

Yes, you can query OpenAlex, Semantic Scholar, and arXiv to fetch metadata and optionally retrieve arXiv full text to enrich your local paper vault and supplement your academic knowledge base.

How do I generate journal recommendations and submission guidance for academic papers?▼

Generate journal recommendations by creating canonical index pages and multi-dimensional tags from your paper vault, which then produce target venue recommendations and revision suggestions based on extracted metadata.

Does this literature survey system work for ongoing academic reviews and idea novelty discovery?▼

Yes, the literature survey system is suitable for ongoing academic reviews, direction landscape reporting, and idea novelty discovery workflows, continuously evolving local Markdown paper collections into structured survey knowledge bases.

What are the limitations of using a Markdown vault for academic direction landscape reporting?▼

The system relies entirely on local Markdown paper files for vault initialization and canonical indexing, meaning direction landscape reporting requires source documents to be pre-converted to Markdown format before ingestion.

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