> Produce a structured summary of an academic working paper or published article. Use this skill when the user shares a paper, asks to summarise a paper, says "what's this paper about", "review this paper", "summarise this for me", or provides a PDF/link to an academic article.
npx skills add https://github.com/aspi6246/Claude-Code-Skills-for-Academics --skill paper-review
When reviewing an academic paper, produce a structured summary covering
every section below. Be specific and precise — name the actual variables,
datasets, and methods used. Do not be vague.
A single sentence capturing the paper's core claim and finding.
Format: "[Authors] show that [X causes/predicts Y] using [method] on [data]."
What specific question does the paper answer? State it as a question.
What is the economic or policy significance? Why should a reader care?
Who are the stakeholders affected? Connect it to broader debates in the
literature if possible.
This is the most important section. Be precise:
The 2-3 main results. Report actual magnitudes where possible
(coefficients, percentage effects), not just "positive and significant."
List 2-3 cited papers that seem important for understanding the
contribution or that are worth reading independently.
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.
Query and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.
Access USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.
Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.
Automated LLM-driven hypothesis generation and testing on tabular datasets. Use when you want to systematically explore hypotheses about patterns in empirical data (e.g., deception detection, content analysis). Combines literature insights with data-driven hypothesis testing. For manual hypothesis formulation use hypothesis-generation; for creative ideation use scientific-brainstorming.
Take aspi6246/paper-review from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.