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cheng-chun-yuan
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paper

Guide researchers through an 8-phase paper development pipeline from topic to submission.

Updated Mar 20, 2026
Search Tags:#research#evaluation#obsidian#notebooklm#paper-writing#claim-evidence#literature-survey
One-click install
npx skills add https://github.com/cheng-chun-yuan/notebooklm-paper-skill --skill paper-cheng-chun-yuan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper
Source: https://github.com/cheng-chun-yuan/notebooklm-paper-skill/tree/main
Command: npx skills add https://github.com/cheng-chun-yuan/notebooklm-paper-skill --skill paper-cheng-chun-yuan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires notebooklm-py, httpx, arxiv, semanticscholar, PyYAML, requests, and includes scripts (resource) components.

What problem does it solve?

Helps researchers move from a raw idea to a submission-ready paper by combining literature discovery, structured note-taking, claim-evidence tracking, experiment planning, draft generation, and pre-submission audits into a single guided workflow. It reduces wasted effort on poorly scoped research, missing baselines, unsupported claims, and last-minute formatting surprises by enforcing phase-specific rubrics and artifact checks.

Core Features & Use Cases

  • Guided 8-phase pipeline: Discover → Position → Architect → Evaluate → Write → Critique → Refine → Ship.
  • Knowledge base integration: Obsidian vault ingestion, per-paper notes, concept synthesis, and a machine-readable CATALOG.
  • NotebookLM support: optional NotebookLM uploads and Q&A for deep document queries.
  • Quality systems: acceptance scorecard, claim-evidence chain, comparison matrix, and binary eval criteria with a Python eval runner.
  • Practical use cases: (1) survey a field and surface blind spots, (2) define a falsifiable contribution and test it, (3) generate and refine a submission-ready draft with simulated peer review.

Quick Start

Run /paper init to create a project and vault, then run /paper discover to begin surveying the literature and building your acceptance scorecard.

Frequently Asked Questions about paper

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

FAQPage Schema
How do I manage a research paper pipeline from literature survey to submission?▼

A research paper pipeline guides you through 8 phases from topic discovery to venue submission. It combines literature discovery, claim-evidence tracking, evaluation, and draft generation to produce a submission-ready manuscript.

What is the best way to track claim-evidence chains during paper writing?▼

Claim-evidence tracking enforces phase-specific rubrics to validate research claims. It links unsupported assertions to their foundational evidence, preventing missing baselines and unsupported claims during manuscript drafting.

Can I use Obsidian and NotebookLM together for literature survey workflows?▼

Obsidian and NotebookLM integrate within the literature survey workflow. Obsidian manages per-paper notes and concept synthesis, while NotebookLM handles optional uploads and deep document Q&A.

How do I run automated evaluations for empirical research experiments?▼

Automated evaluations for empirical research use a Python eval runner with binary criteria. This executes evaluation scripts to test falsifiable contributions and generate acceptance scorecards.

Does arxiv and semanticscholar integration support automated literature discovery?▼

Arxiv and semanticscholar dependencies enable automated literature discovery. Python-backed scripts search and download papers to survey a field, surface blind spots, and build a machine-readable catalog.

How to prepare a research manuscript for venue submission without formatting surprises?▼

Pre-submission audits prepare a research manuscript for venue submission without formatting surprises. The pipeline's final phase enforces artifact checks and simulated peer review before shipping.

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