brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
Find and fix technical debt including duplicated code, dead code, outdated patterns, and code smells. Run at the end of sessions to clean up.
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
Generate research questions from economic phenomena.
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
Search, summarize, and synthesize economics literature.
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
Build and solve Walrasian general equilibrium models with theory derivations and Julia computation.
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
Write and typeset economic models in LaTeX with proper notation.
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
Draft economics papers with proper structure and academic style.
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
Generate publication-ready regression tables in LaTeX.
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
This skill should be used when the user asks to "implement a DiD regression", "write a causal inference pipeline", "set up an event study", "implement instrumental variables", "run a regression discontinuity design", "build a synthetic control model", "implement propensity score matching", "write parallel trends…
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
This skill covers Bayesian estimation and inference in quantitative social science. Use when the user is specifying priors, running MCMC, diagnosing chain convergence, or reporting posterior summaries — including hierarchical models, Bayesian structural models, and small-sample settings where priors regularize.…
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
This skill covers causal inference methods in observational and quasi-experimental settings. Use when the user is implementing, choosing between, or debugging causal identification strategies — including instrumental variables, difference-in-differences, regression discontinuity, synthetic control, or matching…
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
This skill covers causal machine learning methods in applied economics and quantitative social science. Use when implementing or choosing between modern ML-based causal estimators — including double machine learning, DML, partially linear models, interactive regression models, cross-fitting, Neyman orthogonality…
brycewang-stanford/Auto-Empirical-Research-Skills
Skill Claude CodeCodex
This skill covers applied microeconomic empirical methods and research design. Use when the user is selecting an identification strategy, comparing estimators, running diagnostics, designing a research study, or evaluating an empirical strategy. Triggers on "which method", "what estimator", "how to choose", "method…
brycewang-stanford/Awesome-Journal-Skills
Plugin Claude Code
A 12-skill depth pack for AAAI Conference on Artificial Intelligence submissions: topic fit, OpenReview submission checks, author rebuttal, camera-ready, artifacts, reproducibility, supplementary material, review process, writing style, related work, experiments, and workflow. Grounded in official AAAI-26 CFP…
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when positioning an AAAI paper's novelty against archival work, contemporaneous arXiv or workshop papers, and AAAI/IJCAI/NeurIPS/ICML/ICLR neighbors across the broad AI scope, while staying inside AAAI's dual-submission and AI-as-source policy constraints and writing a related-work section legible to…
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when strengthening an AAAI paper's reproducibility checklist (placed after references), experimental traceability, seed and hyperparameter reporting, compute and cost disclosure, dataset access and licensing, code/data ZIP readiness, and the claim-to-evidence map that Phase-1 reviewers use to judge rigor across…
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when explaining or planning around AAAI's two-phase review process, Phase 1 rejection risk, Phase 2 additional reviews, AI-assisted review pilot, author feedback, SPC/AC discussion, and final decisions.
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when auditing an AAAI main technical track submission for OpenReview readiness, double-blind anonymity, page limits, reproducibility checklist, supplementary material, author limits, multiple-submission policy, and AAAI AI-use policy compliance.
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when organizing AAAI supplementary material, including the technical appendix, multimedia appendix, and code/data ZIPs, while respecting that AAAI supplements are due with the paper, treated as immutable after submission, must stay double-blind, and should never hide main-paper-critical evidence from reviewers who…
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when deciding whether a project is a strong AAAI submission across its broad AI scope, should be reframed or routed to a dedicated track such as AI for Social Impact or AI Alignment, or should instead go to IJCAI, NeurIPS, ICML, ICLR, AISTATS, UAI, ACL, CVPR, KDD, CHI, ICRA, or another specialist venue.
brycewang-stanford/Awesome-Journal-Skills
Skill Claude CodeCodex
Use when planning an AAAI project timeline from topic selection through abstract, OpenReview submission, two-phase review, rebuttal, decision, camera-ready, registration, presentation, and public artifact release.
At most 3 mods per repository are shown here — the rest are on their repository pages: