These skills help an agent with academic research workflows. Most come from a Nature-style skills collection, which covers reading, writing and reviewing papers.
19 skills
Create publication-style Matplotlib charts with an AI agent, using scientific plotting conventions, reference scripts and print or vector export guidance.
Build a structured paper-reading card covering methods, evidence chains, limitations and testable research ideas.
Form research questions, search and verify literature, synthesize evidence, and produce a referenced research report.
Review scientific documents for claims, methods, evidence, citations and presentation.
Simulate evidence-grounded peer review with independent reviewer reports and prioritized major and minor concerns.
Frame social-science research questions, literature maps, evidence routes and defensible claims, then review novelty and feasibility.
Run Codex-oriented research, literature review, manuscript revision, study screening and experiment-planning workflows.
Reconstruct a paper’s reasoning, experimental design and evidence limits, with worked examples for key formulas.
Prepare Data and Code Availability statements, repository plans, dataset citations and FAIR metadata checks.
Develop or audit research proposals and plans through evidence, argument and section contracts before drafting.
Prepare point-by-point reviewer responses, revision cover letters, marked manuscripts and consistent revision packages.
Create source-linked Chinese-English Markdown paper readers with aligned text, figures, tables and equations.
Turn scientific papers or reading notes into Chinese PPTX research presentations with source figures and speaker notes.
Retrieve academic full text through open-access, publisher API and authorized institutional or browser access.
Draft manuscript sections and initial-submission materials from supplied evidence, or restructure a scientific argument.
Find Nature and CNS-family papers that support specific manuscript claims, verify sources and export reference-manager files.
Audit statistical reporting across methods, results and figure legends, including replication, uncertainty and multiple comparisons.
Search literature across sources, manage references, verify citations and audit citation impact with explicit evidence.
Automate literature discovery, configurable scoring, reading, delivery and local archival through a scheduled workflow.
Choose research skills for question framing, literature search, paper analysis, citation checks and study screening, with clear scope and traceable evidence.
Use reader and paper-card skills to digest literature, proposal skills to plan studies, and figure skills for publication graphics.