Claude Skills by brycewang-stanford

Build falsifiable causal hypotheses: DAGs, FPCI, equivalence testing.

Draft a senior peer-review report on a social-science manuscript.

Design and diagnose list experiments (item count technique).

Build or audit a literature review: evidence map, gaps, synthesis plan.

Check methods reporting against CONSORT, JARS, DA-RT standards.

Draft scientific introductions: argument logic, framing, multi-experiment coherence.

Pre-submission audit: argument, numerics, refs, writing, figures, replication.

Clean post-OCR text: correction, QA, multilingual handling, provenance.

Write pre-analysis plans: PAP structure, registry, analysis strategy.

Scaffold or audit a social-science replication package at a target directory. Generates folder structure, README, master.R, figure/table crosswalk, codebook template, LICENSE placeholder, and pre-release checklist. Adapted from Yusaku Horiuchi's replication-package-guide with FAIR-principle integration; platform-neutral (Harvard Dataverse, OSF, Zenodo, GitHub releases, institutional archives).

Design survey instruments: questions, scales, flow, social desirability.

Design and format publication-quality tables: column order, row grouping, notes, precision, reproducibility.

LLM-based text classification: codebook, validation, agreement statistics.

Structural topic modeling: STM spec, topic count, coherence-exclusivity.

VLM-based OCR pipeline: model selection, prompts, architecture, evaluation.

Patterns for Bayesian inference in R using brms, including multilevel models, DAG validation, and marginal effects. Use when performing Bayesian analysis.

R object-oriented programming guide for S7, S3, S4, and vctrs. Use when designing R classes or choosing an OOP system.

R package development guide covering dependencies, API design, testing, and documentation. Use when developing R packages.

R performance best practices including profiling, benchmarking, vctrs, and optimization strategies. Use when optimizing R code.

R style guide covering naming conventions, spacing, layout, and function design best practices. Use when writing R code.

rlang metaprogramming patterns for data-masking, injection operators, and dynamic dots. Use when writing functions that use tidy evaluation.

Test-driven development workflow for R using testthat. Use when writing new features, fixing bugs, or refactoring code. Enforces test-first development with 80%+ coverage.

Modern tidyverse patterns for R including pipes, joins, grouping, purrr, and stringr. Use when writing tidyverse R code.

Expert economics paper writing assistant synthesizing advice from 50+ top guides by Cochrane, McCloskey, Shapiro, Head, Bellemare, Goldin, Glaeser, Kremer, and other leading economists. USE THIS SKILL whenever the user writes, edits, reviews, rewrites, or structures any economics paper, thesis, job market paper, abstract, introduction, conclusion, results section, literature review, or referee response. Also handles LaTeX formatting, presentations, and paper audits. Covers all paper types (ap...

Query and analyze SEC filings using EdgarTools

Structured policy briefing note (1-2 pages). Issue, background, analysis, options, recommendation. UK GES, Australian Treasury, consulting formats. Auto-populates from econstack data skills.

Cost-benefit analysis. Produces economic NPV and financial NPV side by side, with BCR, optimism bias (with mitigation), Marginal Excess Tax Burden, real-terms rebasing, WELLBY / QALY / VPF wellbeing valuation, sensitivity, switching values, EANC for unequal-life options, validation gate, and a one-line headline verdict (socially worthwhile vs financially self-sustaining). Backed by the greenbook R package (HM Treasury Green Book primitives) when available, with graceful fallback. Supports HMT...

Audit economic analysis outputs (fiscal briefings, macro briefings, market research, longlists, and other quantitative economic documents) against methodology standards, academic literature, and common errors. Runs structured checks across core categories including counterfactual, additionality, discounting, double counting, distributional analysis, Aqua Book RIGOUR, and Flyvbjerg-style strategic misrepresentation detection. Returns a RAG scorecard with issues ranked by severity.

Public finances briefing. Supports UK, US, and Australia. Produces a single compact briefing on borrowing, debt, receipts, spending, and fiscal rules. Optional debt sustainability analysis via the debtkit R package. User-selectable sub-components and multi-format export.

Brainstorm a longlist of benefits and costs for a project. Outputs two clean tables (benefits and costs), each with materiality (H/M/L), a cash flow tag (cash in / cash out / non-cash), a quantification method, and a monetisation method. Supports HMT Green Book, EU Better Regulation Guidelines, World Bank, Asian Development Bank, and the Victorian Treasury High Value High Risk (HVHR) framework.

Macroeconomic monitor. Supports UK, US, Euro area, and Australia. Pulls GDP, inflation, employment, wages, rates, trade, housing, and fiscal data. Each country follows its central bank's reporting structure. Produces a single clean briefing with a traffic-light assessment and user-selectable sub-components.

Industry and market research. Market sizing, structure, competition, regulation, supply chains, pricing, M&A. Produces a single compact, source-cited research report with Porter's Five Forces, HHI / CR4, PESTLE, and trade flows. Supports UK, US, EU, Australia, and global scope, with multi-geography comparison.

Use when working on any empirical academic research context — paper writing, data analysis, literature review, or any task involving citations, results, or publication artifacts. Establishes non-negotiable principles that govern all other superpapers skills.

Use when starting a new research project, exploring a research idea, deciding whether a question is viable, or before touching code or data for a new paper. Runs a research-focused brainstorm that clarifies research question, identification strategy, data feasibility, and contribution before any implementation.

Use when adding citations to a .bib file, importing references by DOI, cleaning a bibliography, detecting duplicate entries, or normalizing citation keys. Uses direct .bib manipulation with CrossRef API for metadata resolution — no external tool dependencies.

Use when compiling a LaTeX paper, debugging LaTeX errors, building a paper PDF, or when a .tex file fails to produce output. Handles engine detection (xelatex vs pdflatex), bibliography systems (biber vs bibtex), and multi-pass compilation.

Use when collecting data for a research project, downloading time series, building a dataset, accessing economic or social data APIs, or scraping data from a non-API source. Handles source discovery, respectful collection, local caching, and manifest documentation.

Use when a research implementation plan exists in docs/superpapers/plans/ and the user is ready to execute it — collecting data, running analysis, producing outputs, writing the paper. Orchestrates task execution with replication-driven verification and two-stage review at phase boundaries.

Use when preparing a paper for submission to a specific journal, checking formatting requirements, parsing instructions for authors, building a submission checklist, or adapting a paper to a journal template. Fetches the journal's official guidelines via web and produces a verifiable checklist.

Use when choosing a target journal for a paper, comparing journal rankings, asking "where should I submit this", or building a submission strategy across multiple journals. Field-agnostic — detects the paper's research area and suggests appropriate outlets across tiers.

Use when the user asks to search for papers, review literature, find references on a topic, verify a paper exists, or build a bibliography. Enforces web verification of every citation via web fetch to prevent hallucinated references.

Use when a paper is complete or near-complete and a holistic pre-submission audit is needed. Cross-cuts text, code, tables, figures, results, citations, and reproducibility in a single pass and produces a persistent audit report. Works standalone on papers written outside the plugin.

Use when drafting, rewriting, reviewing, or auditing prose for any section of an empirical academic paper (Abstract, Introduction, Methods, Data, Results, Discussion, Conclusion) or specialized output (job market paper, grant proposal, policy brief, referee response).

Use when starting empirical analysis, creating a data pipeline, generating results, or when data or model specifications change. Enforces end-to-end reproducibility — every number in the paper must be regenerable from raw data by a script with a fixed seed. Replaces TDD for the research domain.

Use when a main specification has produced a result, when preparing a paper appendix, when a reviewer requests robustness, or before declaring any empirical finding final. Guides selection of design-appropriate checks without mandating a fixed checklist.

Use when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data. Guides the process (assumptions, estimation, reporting, diagnostics) without forcing a fixed method list.

Use when generating a LaTeX results table, creating a figure for a paper, formatting descriptive statistics, preparing regression output for publication, or producing vector-quality graphics. Enforces booktabs, threeparttable, vector PDFs, and script-generated output.

Use when a research design spec exists and the user is ready to translate it into a concrete implementation plan with phased tasks, artifacts, and verification criteria. Produces a research execution plan organized in canonical research phases — collection, preparation, analysis, robustness, writing, submission.

Confirmatory hypothesis testing matched to pre-registration, with full assumption testing, effect sizes, confidence intervals, and APA 7th formatted output. Supports OLS/GLM regression, panel regression (fixest), mixed models (lme4), SEM/CFA (lavaan), meta-analysis (metafor), and delegates PROCESS models to /process-model. Reads pre-registration to align planned analyses, flags deviations, and generates decision log entries for post-hoc choices. Use when the user says "test hypotheses," "run ...

Produce documented data cleaning scripts that log every transformation with N before/after each step, generate a CONSORT-style exclusion flow diagram, create decision log entries for every subjective choice, compute scale reliability and composites, and write cleaned data to data/processed/. Never modifies raw data. Use when the user says "clean data," "prepare data," "apply exclusion criteria," "handle missing data," "create composites," "data preprocessing," or when /data-validate found iss...