brycewang-stanford/Auto-Empirical-Research-Skills - Seite 10

compile-latex

Compile a LaTeX manuscript with pdflatex (3 passes + bibtex). Use when compiling the research paper.

Quellsprache: Englisch

data-analysis

End-to-end R data analysis workflow from exploration through regression to publication-ready tables and figures.

Quellsprache: Englisch

devils-advocate

Challenge research design decisions, assumptions, and methodology choices with specific critical questions. Helps strengthen the paper before submission.

Quellsprache: Englisch

econometrics-julia

Julia-based econometric and structural estimation for computationally intensive tasks. Use for structural models, maximum likelihood, GMM, numerical optimization, simulations, and high-performance computing. Covers DataFrames.jl, FixedEffectModels.jl,…

Quellsprache: Englisch

econometrics-r

R-based econometric analysis for academic research. Use when writing R code for panel data, difference-in-differences, instrumental variables, spatial econometrics, or regression analysis. Covers data.table, fixest, sf, modelsummary, and publication-ready…

Quellsprache: Englisch

interview-me

Interactive interview to formalize a research idea into a structured specification with hypotheses and empirical strategy.

Quellsprache: Englisch

lit-review

Structured literature search and synthesis with citation extraction and gap identification.

Quellsprache: Englisch

proofread

Run the proofreading protocol on manuscript files. Checks grammar, typos, overflow, consistency, and academic writing quality. Produces a report without editing files.

Quellsprache: Englisch

research-ideation

Generate structured research questions, testable hypotheses, and empirical strategies from a topic or dataset.

Quellsprache: Englisch

review-julia

Run the Julia code review protocol on Julia scripts. Checks code quality, type stability, parallel computing patterns, and scientific computing standards. Produces a report without editing files.

Quellsprache: Englisch

review-paper

Comprehensive manuscript review covering argument structure, identification strategy, econometric specification, citation completeness, and potential referee objections.

Quellsprache: Englisch

review-r

Run the R code review protocol on R scripts. Checks code quality, reproducibility, domain correctness, and professional standards. Produces a report without editing files.

Quellsprache: Englisch

stata

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…

Quellsprache: Englisch

validate-bib

Validate bibliography entries against citations in all manuscript files. Find missing entries and unused references.

Quellsprache: Englisch

analyze

End-to-end data analysis dispatching Coder and Data-engineer for implementation, coder-critic for review. Supports R, Stata, Python, Julia. Replaces /data-analysis.

Quellsprache: Englisch

discover

Discovery phase combining research interviews, literature search, data discovery, and ideation. Routes to appropriate agents based on arguments. Replaces /interview-me, /lit-review, /find-data, /research-ideation.

Quellsprache: Englisch

new-project

Full research pipeline from idea to paper. Orchestrates all phases — discovery, strategy, analysis, writing, peer review, and submission. Use when starting a new research project from scratch.

Quellsprache: Englisch

review

All quality reviews — routes to appropriate critics based on target file type and flags. Replaces /paper-excellence, /proofread, /econometrics-check, /review-r, /review-paper.

Quellsprache: Englisch

revise

R&R cycle — classify referee comments and route to appropriate agents. Replaces /respond-to-referee.

Quellsprache: Englisch

strategize

Design identification strategy or pre-analysis plan. Dispatches Strategist (proposer) and strategist-critic (validator). Replaces /identify and /pre-analysis-plan.

Quellsprache: Englisch

submit

Submission pipeline — journal targeting, replication package, audit, and final gate. Replaces /submit, /target-journal, /audit-replication, /data-deposit.

Quellsprache: Englisch

talk

Create and audit presentations (Beamer or Quarto RevealJS). Combines talk creation, visual audit, and compilation. Replaces /create-talk, /visual-audit, /compile-latex (for talks).

Quellsprache: Englisch

tools

Utility commands — commit, compile, validate-bib, journal, context-status, deploy, learn. Replaces individual utility skills.

Quellsprache: Englisch

write

Draft academic paper sections with notation protocol, anti-hedging, and humanizer pass. Replaces /draft-paper and /humanizer.

Quellsprache: Englisch

agent-authoring

Guide for creating DAAF agent definition files. Covers 12-section template, hook registration, skills-in-frontmatter, integration checklist. Use when adding or revising agents. For SKILL.md files, use skill-authoring instead.

Quellsprache: Englisch

daaf-orchestrator

Operational framework for the DAAF orchestrator. Defines engagement modes, confirmation protocol, subagent dispatch, context budget, and reference-loading. Loaded exclusively by the orchestrator — not for subagents or user questions.

Quellsprache: Englisch

data-scientist

Data science methodology for Python research: EDA, validation, causal inference (IV, DiD, RD, synthetic control), clustering/PCA/UMAP, supervised ML, geospatial, visualization. Method selection guidance. For syntax, load tool-specific skills.

Quellsprache: Englisch

education-data-context

Interpretation guidance for Urban Institute Portal datasets. Coded values (-1/-2/-3), year definitions, grade encoding, suppression, licensing, cross-source joins. Use when interpreting Portal data before analysis. Routes to source-specific skills.

Quellsprache: Englisch

education-data-explorer

Discovers education data from Urban Institute Portal: endpoints, variables, year coverage, join keys (CCD, IPEDS, CRDC, Scorecard, SAIPE). Use to map questions to data. Load before education-data-query — discovery here, download there.

Quellsprache: Englisch

education-data-query

Downloads education datasets from configured mirror sources (parquet/CSV) with local Polars filtering. Use when writing fetch scripts or retrieving CCD, IPEDS, CRDC, SAIPE data. Load after education-data-explorer — retrieval here, not discovery.

Quellsprache: Englisch

education-data-source-campus-safety

CSS — annual Clery Act crime/fire safety for Title IV institutions. Portal: hate crimes only (2005-2021); primary offenses, VAWA, arrests, fire safety need ope.ed.gov directly. Use for campus crime analysis. Identified by IPEDS unitid.

Quellsprache: Englisch

education-data-source-ccd

CCD — federal universe of all U.S. public K-12 schools (~100K) and districts (~18K). Enrollment, staffing, finance, directory data (1986-present). Use for public school analysis by grade/race/sex. Public only; excludes private and postsecondary.

Quellsprache: Englisch

education-data-source-crdc

CRDC — biennial OCR survey of all U.S. public schools (2011-2021). Discipline, course access, harassment, restraint/seclusion by race/sex/disability/EL. Use for civil rights and equity analysis. 2020-21 COVID-impacted; 2011-14 sampled, not universe.

Quellsprache: Englisch

education-data-source-eada

EADA — college athletics gender equity (~2,000+ institutions, 2002-2021). Participation, coaching, salaries, expenses, revenues, athletic aid by gender. Not Title IX compliance data. No sector column; join IPEDS on unitid for institution type.

Quellsprache: Englisch

education-data-source-edfacts

EDFacts — K-12 outcomes: assessment proficiency, ACGR graduation rates, ESSA accountability at school/district level (2009-2020). Within-state trends and subgroup gaps. Complements CCD with outcome data. Cannot compare across states — use NAEP.

Quellsprache: Englisch

education-data-source-fsa

FSA — Title IV aid at institution level (~5,500 institutions, 1999-2021). Pell Grants, Direct/PLUS loans, campus-based aid, financial responsibility scores, 90/10 metrics. Use for aid distribution, loan volume, or for-profit analysis. By unitid.

Quellsprache: Englisch

education-data-source-ipeds

IPEDS — primary federal postsecondary data (~6,500 institutions, 1980-present): enrollment, completions, graduation rates, finance, aid, admissions, HR. For college/university analysis. Grad rates = first-time full-time; finance needs GASB/FASB care.

Quellsprache: Englisch

education-data-source-meps

MEPS — Urban Institute modeled school-level poverty (% at 100% FPL), from CCD + SAIPE (public schools, 2009-2022, 2-3yr lag). Use when FRPL is unreliable due to CEP. Consistent cross-state measurement. Public schools only.

Quellsprache: Englisch

education-data-source-nacubo

NACUBO endowment data (~650 institutions, 2012-2022). Portal: 7 columns only (total endowment, per-FTE, YoY change). Use for endowment size/trends. Full investment/spending needs direct NACUBO access. For all-institution coverage use IPEDS finance.

Quellsprache: Englisch

education-data-source-nccs

NCCS — Form 990 data for private nonprofit colleges (Portal: IPEDS-matched, 1993-2016). Revenue, expenses, assets, endowment, governance beyond IPEDS. Use when IRS financial depth needed. Portal ends 2016; public institutions excluded (no Form 990).

Quellsprache: Englisch