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SkillsMP has collected 1,111 skills from brycewang-stanford/Auto-Empirical-Research-Skills. Open a skill to review its source and details.
Showing 40 of 1,111 collected skills.
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal…
中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and…
Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool…
Use when auditing a finished or near-finished AER, AER:Insights, or AEJ manuscript for internal consistency: headline numbers across abstract, introduction, results, and tables; sample sizes; log-point and percentage-point conversions; cross-references; and…
Use when selecting, implementing, or stress-testing the causal identification strategy for an empirical economics manuscript — difference-in-differences (including staggered designs), instrumental variables (including weak-IV-robust inference), regression…
Use when drafting or rewriting the introduction of an economics manuscript targeted at AER, AER:Insights, or an AEJ, or when compressing an abstract to the mandatory 100-word limit. Implements the Keith Head / Bellemare five-paragraph formula and AER-specific…
Use when positioning a manuscript against the existing economics literature, building the antecedents map for the introduction, deciding what to cite, or verifying that every reference in the bibliography is real, correctly attributed, and cited to the…
Use when drafting or revising the body sections of an AER, AER:Insights, or AEJ manuscript — institutional background, data, empirical strategy, results, mechanisms, and conclusion. Covers equation conventions, results-paragraph narration, magnitude…
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is…
Use when responding to a Revise & Resubmit decision from AER, AER:Insights, or an AEJ, and a point-by-point response letter plus aligned manuscript revisions are needed. Handles triage, the concede / clarify / push-back decision, and the response-letter…
Use when a complete draft exists and needs an adversarial internal review before submission — simulating the AER desk screen and three referee reports with calibrated severity, scoring the paper against the editorial rubric, and producing a prioritized revise…
Use when assembling the AEA Data and Code Availability deposit for an AER, AER:Insights, or AEJ acceptance, writing the README, or auditing a replication package before the AEA Data Editor review. Implements the current AEA policy, including the February 2026…
Use when the main empirical results exist but the manuscript lacks the robustness, heterogeneity, mechanism, and placebo checks that AER referees will demand. Apply after aer-identification and before aer-introduction so that the value-added paragraph can…
Use when aer-identification has fixed the design, after methodology choice and before aer-robustness or aer-tables-figures, to run an AER-track analysis with StatsPAI — the agent-native Python engine and MCP server for causal inference, robustness,…
Use when running the final pre-submission audit for an AER, AER:Insights, or AEJ manuscript — length, format, cover letter, per-author disclosure statements, file packaging, and routing among the AEA journal family. Apply immediately before clicking submit.
Use when constructing or revising regression tables, descriptive statistics tables, or figures after results are estimated and before submission for an AER, AER:Insights, or AEJ manuscript. Implements AER booktabs house style, regression-table layout, and…
Use when evaluating whether a research idea clears the AER top-5 bar, when routing between AER, AER:Insights, and the AEJ family, or when sharpening a fuzzy contribution sentence into one publishable claim. Apply before any writing begins.
Use when deciding which AER-skills sub-skill to use next, before choosing a specialized skill or after a user asks how to sequence manuscript work from topic selection through rebuttal for AER, AER:Insights, or AEJ journals. Routes — does not replace — the…
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying…
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style**…
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth…
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance +…
Integrate AI tools into economic research, teaching, and policy analysis with attention to privacy and reproducibility.
Coordinate writing, revision, and submission workflows for collaborative academic and policy documents.
Create concise policy briefs that translate research into actionable recommendations for policymakers and stakeholders.
Strategic research leadership for designing high-impact research agendas, coordinating teams, and translating research into policy and institutional influence.
Plan, draft and refine research papers with reproducible analysis and publication-ready manuscripts.
Run a 6-agent pre-submission panel review for a grant proposal targeting a specified funder or program
Run a 6-agent pre-submission review of a pre-analysis plan (PAP) for a specified registration target or journal
Review research code for reproducibility and quality, extract the paper's main empirical claims, compare paper to code, and write a constructive markdown report. Designed for social science / economics projects with LaTeX papers and Stata, R, or Python code.
Run a fast 2-agent pre-submission check for an economics paper — focuses on contribution, identification, and causal overclaiming. Completes in ~1 minute.
Run a 6-agent pre-submission referee report for an academic paper targeting a specified journal
Standardized Python & Stata coding practices for empirical research projects
Document datasets, variables, sources, and merge keys for replication
Summarize academic papers, extract key findings, and identify research gaps
Project directory organization and script naming conventions for research
Structure responses to referee reports for R&R submissions
Checklist of empirical robustness tests for finance/economics papers
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.