academic-research-skills

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. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.

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 Cowork prompt", "rewrite for Cowork", or "make this a Cowork prompt". Outputs a single code block with the rewritten prompt following the GOAL/CONTEXT LOADING/IDENTITY/SUCCESS CRITERIA/INPUTS/CONSTRAINTS/CHECKPOINT RULE structure.

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", "plan research", or mentions research project initiation phase. Provides comprehensive guidance for research startup workflow from idea generation to planning.

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 observations yet. For formulating testable hypotheses from data use hypothesis-generation.

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 citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.

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 wants to verify, clean up, canonicalize, or find DOIs for those references — triggers include "verify bibliography", "match these references", "find DOIs for this reference list", "canonicalize my citations", "clean up the reference list against Crossref", "check these citations", or any pasted block of academic references accompanied by a request to normalize them.

Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.

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 type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.

Panel data analysis with Python using linearmodels and pandas.

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.

Run IV, DiD, and RDD analyses in R with proper diagnostics

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 patterns, group dynamics, inequality, socialization, social change, and collective action. Use when: Social movements, inequality, cultural trends, group behavior, institutions, identity, social change. Evaluates: Social structures, power relations, inequality, norms, group dynamics, cultural patterns, social change.

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 [method]?" or "Show me code for [technique]" — including: entropy balancing, propensity score matching (PSM), difference-in-differences (DiD), regression discontinuity (RDD), instrumental variables (IV), event studies (CAR/BHAR), survival analysis, Fama-MacBeth regressions, bootstrap, quantile regression, reghdfe/xtreg/areg, clustering standard errors, fixed effects, esttab/outreg2 table formatting, winsorization, leads/lags. Users can specify their variables (e.g., treatment, outcomes, controls) and receive adapted syntax. NOTE: This skill provides code patterns from published papers, not research design advice.

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.

Clean and transform messy data in Stata with reproducible workflows

Run regression analyses in Stata with publication-ready output tables.

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 syntax.

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 patterns. Use this skill whenever the user asks you to write, debug, or explain Stata code.

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, sp.balance_table, sp.balance_panel), estimand-first research-question DSL (sp.causal_question), LLM-assisted DAG discovery (sp.llm_dag_propose/validate/constrained), one-call orchestration (sp.causal), classical estimators (OLS, IV, DID, staggered DID, RDD, PSM, SCM), ML causal (DML, Causal Forest, Meta-Learners, TMLE), neural causal, text causal (sp.causal_text), and diagnostics + robustness (sp.diagnose, sp.spec_curve, sp.honest_did). Use when the user asks to run a full empirical analysis, decide which estimator to use ("DID vs RD vs IV?"), explore models via DAG, estimate treatment effects, evaluate policy, run observational studies, or apply any of the listed econometric methods in Python. Every function returns structured result objects with self-describing sch

Fetch economic data from FRED, World Bank, and other APIs

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.

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.

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 OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.

Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. No API keys required.

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 research, investigation, or needs synthesized analysis with citations.

Search, summarize, and synthesize economics literature

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 comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

Create Excalidraw diagram JSON files that make visual arguments. Use when the user wants to visualize workflows, architectures, or concepts.

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 on requests like "write a case about X", "create an HBS case on Y", or "develop a teaching case for Z". Outputs immersive, decision-focused narratives with supporting exhibits and teaching notes.

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 posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detect

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, and poster-specific best practices for visual communication.

Generate publication-ready regression tables in LaTeX.

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 research-lookup for data gathering, and multi-framework strategic analysis including Porter Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.

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 dissemination, conference preparation, creating explorable academic homepages, generating video abstracts, or producing print-ready posters from LaTeX or PDF sources.

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 files, PDFs, documentation, configs, or any readable content. Respond in the user's language.

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 sizes, methodology alignment, structural formatting, cross-document coherence, and common pitfalls. TRIGGER when: submitting to journal, responding to R&R, finalizing working paper, user mentions "consistency check", "pre-submission", "audit paper", "check my manuscript", or asks to verify cross-references before submission.

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", or mentions claims that need validation.

Defamiliarization audit for empirical output. Systematically interrogates every feature of a figure, table, or set of results — not just the main finding. Named for Jason Fletcher, who asked about the spike at t=1 when everyone else was looking at t=2. Use when you have output and are about to interpret or report it.

This skill should be used when the user asks to "review paper quality", "check paper completeness", "validate paper structure", "self-review before submission", or mentions systematic paper quality checking. Provides comprehensive quality assurance checklist for academic papers.

Systematic peer review toolkit. Evaluate methodology, statistics, design, reproducibility, ethics, figure integrity, reporting standards, for manuscript and grant review across disciplines.