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SkillsMP は franklee16/academic-research-skills から 69 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 69 件中 40 件を表示しています。
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework.…
原文の言語: 英語
Transforms raw user requests into structured, outcome-focused prompts for Claude Cowork. Use when the user wants to optimize or rewrite a prompt for Cowork, needs help structuring a multi-step task for autonomous execution, or says things like "optimize this…
原文の言語: 英語
This skill should be used when the user asks to "brainstorm research ideas", "use 5W1H framework", "identify research gaps", "conduct gap analysis", "start research project", "conduct literature review", "define research question", "select research method",…
原文の言語: 英語
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific…
原文の言語: 英語
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify…
原文の言語: 英語
Match a pasted list of academic references against the Crossref REST API and produce a four-column markdown table (original, matched, confidence, flags) with canonical APA citations and DOIs. Use whenever the user pastes a bibliography or reference list and…
原文の言語: 英語
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
原文の言語: 英語
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file…
原文の言語: 英語
Panel data analysis with Python using linearmodels and pandas.
原文の言語: 英語
R statistical analysis for publication-ready sociology research. Guides you through phased workflows for DiD, IV, matching, panel methods, and more. Use when doing quantitative analysis in R for academic papers.
原文の言語: 英語
Run IV, DiD, and RDD analyses in R with proper diagnostics
原文の言語: 英語
Analyzes events through sociological lens using social structures, institutions, stratification, culture, norms, collective behavior, and multiple theoretical perspectives (functionalist, conflict, symbolic interactionist). Provides insights on social…
原文の言語: 英語
STATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal of Accounting Research) replication files (2017-2025). Use when the user asks procedural questions like "How do I implement…
原文の言語: 英語
Stata statistical analysis for publication-ready sociology research. Guides you through phased workflows for DiD, IV, matching, panel methods, and more. Use when doing quantitative analysis in Stata for academic papers.
原文の言語: 英語
Clean and transform messy data in Stata with reproducible workflows
原文の言語: 英語
Run regression analyses in Stata with publication-ready output tables.
原文の言語: 英語
Use when writing, running, or debugging Stata code, do files, ado files, packages, or Mata programs in this environment. Use when loading Stata datasets, running regressions, managing data, developing Stata commands or packages, or working with Stata/Mata…
原文の言語: 英語
Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 17+ community packages (reghdfe, estout, did, rdrobust, etc.). Covers syntax, options, gotchas, and idiomatic…
原文の言語: 英語
Agent-native one-stop toolkit for the full empirical data-analysis pipeline in Python (v1.6+). 900+ functions, one import (`import statspai as sp`), unified API. Covers the complete loop after data cleaning — descriptive stats & EDA (sp.sumstats,…
原文の言語: 英語
Fetch economic data from FRED, World Bank, and other APIs
原文の言語: 英語
Skill for accessing, downloading, and parsing financial filings from the SEC EDGAR database. Helps users retrieve 10-K, 10-Q, 8-K, and other forms using the SEC's JSON API.
原文の言語: 英語
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
原文の言語: 英語
Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native…
原文の言語: 英語
Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. No API keys required.
原文の言語: 英語
Comprehensive research assistant that synthesizes information from multiple sources with citations. Use when: conducting in-depth research, gathering sources, writing research summaries, analyzing topics from multiple perspectives, or when user mentions…
原文の言語: 英語
Conduct preliminary research on a topic and generate research outline. For academic research, benchmark research, technology selection, etc.
原文の言語: 英語
Conduct preliminary research on a topic and generate research outline. For academic research, benchmark research, technology selection, etc.
原文の言語: 英語
对目标话题进行初步调研，生成调研outline。用于学术调研、benchmark调研、技术选型等场景。
原文の言語: 中国語
Search, summarize, and synthesize economics literature
原文の言語: 英語
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or…
原文の言語: 英語
Create Excalidraw diagram JSON files that make visual arguments. Use when the user wants to visualize workflows, architectures, or concepts.
原文の言語: 英語
Create Harvard Business School-style case studies on financial market events, products, or investment decisions. Use when the user wants to write a teaching case about a financial event, market phenomenon, investment product, or corporate decision. Triggers…
原文の言語: 英語
Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific…
原文の言語: 英語
Create professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration,…
原文の言語: 英語
Generate publication-ready regression tables in LaTeX.
原文の言語: 英語
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with…
原文の言語: 英語
This skill should be used when converting academic papers into promotional and presentation formats including interactive websites (Paper2Web), presentation videos (Paper2Video), and conference posters (Paper2Poster). Use this skill for tasks involving paper…
原文の言語: 英語
Socratic method teaching skill that guides users to discover answers themselves through questioning, never giving direct answers. TRIGGER when: user's message contains 'socratic', 'Socrates', or '소크라테스'. Works with any knowledge asset — codebases, markdown…
原文の言語: 英語
Systematic pre-submission consistency audit for academic manuscripts in accounting/finance. Performs exhaustive checks across 10 categories: cross-references (tables, figures, equations, citations), table/figure consistency, variable definitions, sample…
原文の言語: 英語
Systematic fact verification and misinformation identification using evidence-based analysis. Use when: verifying claims, checking facts, identifying misinformation, evaluating source credibility, or when user asks to "fact check", "verify", "is this true",…
原文の言語: 英語