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cccskills

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5,900 件 ・ 関連度順

概要と使いどころ

ml-causal

無料

Econometrics skill for machine learning methods in causal inference. Activates when the user asks about: "causal forest", "generalized random forest", "GRF", "double machine learning", "DML", "debiased machine learning", "LASSO for variable selection", "post-LASSO", "heterogeneous treatment effects", "CATE", "conditional average treatment effect", "BLP analysis", "CLAN analysis", "causal tree", "honest estimation", "因果森林", "双重机器学习", "异质性处理效应", "条件平均处理效应", "LASSO变量选择", "机器学习因果推断", "去偏机器学习"

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

table

無料

Econometrics skill for creating publication-quality LaTeX regression and summary tables. Activates when the user asks about: "regression table", "LaTeX table", "esttab", "stargazer", "modelsummary", "publication table", "format results", "multi-panel table", "journal table", "export regression results", "table formatting", "回归表格", "LaTeX表格", "结果导出", "论文表格", "回归结果格式化", "多模型表格"

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Access NBER working papers and economic research datasets

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

所有联网操作必须通过此 skill 处理,包括:搜索、网页抓取、登录后操作、网络交互等。触发场景:用户要求搜索信息、查看网页内容、访问需要登录的网站、操作网页界面、抓取社交媒体内容(小红书、微博、推特等)、读取动态渲染页面、以及任何需要真实浏览器环境的网络任务。

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Econometrics skill for Synthetic Control Method (SCM). Activates when the user asks about: "synthetic control", "SCM", "synthetic counterfactual", "donor pool", "placebo test", "in-space placebo", "in-time placebo", "MSPE ratio", "Abadie Diamond Hainmueller", "augmented synthetic control", "penalized SCM", "synthetic DID", "合成控制", "合成控制法", "捐助池", "安慰剂检验", "合成反事实", "合成DID", "政策评估"

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

This skill covers formal identification arguments and proofs in structural and reduced-form econometrics. Use when the user needs to prove or formalize that a parameter is identified — including writing identification propositions, stating regularity conditions, deriving rank conditions, or showing observational equivalence fails. Triggers on "identification proof", "identification argument", "identify the parameter", "show identification", "identification condition", "exclusion restriction proof", "rank condition", "order condition", "identification strategy formal", "nonparametric identification", "parametric identification", "local identification", "global identification", "observational equivalence", "identification at infinity", "completeness condition", "regularity conditions", "Rothenberg", "proof of identification", "identification result", "identified parameter", "point identified", "set identified", "partial identification".

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

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 estimators. Triggers on "causal effect", "identification strategy", "instrumental variable", "2SLS", "GMM", "difference-in-differences", "DiD", "staggered treatment", "regression discontinuity", "RDD", "synthetic control", "matching", "propensity score", "IPW", "AIPW", "doubly robust", "LATE", "ATT", "ATE", "parallel trends", "exclusion restriction", "first stage", "weak instruments", or "endogeneity".

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

stata

無料

Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 20 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.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

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. Triggers on "Bayesian estimation", "Bayesian inference", "MCMC", "Markov chain Monte Carlo", "Stan", "PyMC", "NumPyro", "prior", "posterior", "credible interval", "Bayesian structural", "Bayesian BLP", "Bayesian DSGE", "hierarchical model", "random effects Bayesian", "posterior predictive check", "Bayes factor", "prior predictive check", "NUTS", "HMC", "Hamiltonian Monte Carlo", "R-hat", "rhat", "effective sample size", "ESS", "Bayesian calibration", "posterior distribution", "prior elicitation", "weakly informative prior", "brms", "rstanarm", "cmdstanpy", "pymc", "arviz".

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Econometrics skill for Regression Discontinuity Design (RDD). Activates when the user asks about: "regression discontinuity", "RDD", "RD design", "sharp RDD", "fuzzy RDD", "running variable", "forcing variable", "cutoff", "bandwidth selection", "local linear regression", "McCrary test", "density test", "RDROBUST", "continuity assumption", "donut hole RDD", "geographic RDD", "断点回归", "回归不连续", "运行变量", "截断值", "带宽选择", "精确断点", "模糊断点", "密度检验", "局部线性回归"

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

causal-ml

無料

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, debiased ML, causal forests, generalized random forest, GRF, honest causal trees, AIPW with machine learning, doubly robust with machine learning, DR-Learner, T-Learner, S-Learner, X-Learner, meta-learners, heterogeneous treatment effects, conditional average treatment effect, CATE, HTE, high-dimensional controls, LASSO controls, post-LASSO, post-double selection, Belloni-Chernozhukov-Hansen, Riesz representer, Chernozhukov, sample splitting, econml, DoubleML package, or any combination of machine learning and causal inference.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

grillme

無料

苏格拉底诘问式研究选题Skill。通过连续追问帮你厘清研究思路、聚焦研究子领域、明确研究问题(RQ),识别出未被研究过的新意选题。触发词:帮我选题/研究问题不清晰/想做一个有新意的论文/不断问我问题/厘清思路

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Econometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "staggered DID", "event study regression", "two-way fixed effects DID", "callaway santanna", "sun and abraham", "双重差分", "倍差法", "平行趋势", "处理组", "对照组", "政策评估", "事件研究", "交错DID", "渐进处理"

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

学术引用核查Skill。要求每条引用必须定位到PDF原页,区分直接引用/间接引用,找不到原文则标注"待核"。触发词:引用核查/检查引用/citation check/核实文献/引用 fidelity

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Use this skill whenever the user wants to conduct an event study, create event study plots, test for parallel trends, implement difference-in-differences designs, or work with any panel data estimation that involves pre/post treatment comparisons. Trigger on phrases like "event study", "parallel trends", "pre-trends", "dynamic treatment effects", "leads and lags", "TWFE", "two-way fixed effects", "staggered adoption", "staggered treatment", "difference-in-differences", "DiD", "Sun and Abraham", "Callaway and Sant'Anna", "de Chaisemartin", "Borusyak", "did_multiplegt", "fixest", "did2s", "bacon decomposition", or any reference to plotting coefficients around a treatment event. Also trigger when the user uploads panel data and wants to estimate treatment effects with variation in treatment timing. All code is in R.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

LaTeX回归表格生成Skill。辅助生成符合AER/QJE等顶刊格式的三线表,包括标准误聚类标注、显著性星标、固定效应标注。触发词:LaTeX表格/回归表/三线表/table制作/latex table

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

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 (applied, theory, structural, mixed) and all sections.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

do-agent

無料

This skill should be used when the user asks to "/do-agent", asks for "Execute complex tasks using multi-agent architecture with context protection", or needs the workflow previously provided by the /do-agent slash command.

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

PROACTIVE SKILL — automatically apply whenever writing, generating, or editing any text that is mainly in Chinese. No user trigger needed. Also use when the user explicitly asks to "fix Chinese", "修改中文", "去翻译腔", "去AI味", "fix Chinese formatting", or "review Chinese text". Eliminates AI-sounding expressions and translation artifacts. Enforces Chinese-English mixed formatting rules (spacing, punctuation, bold formatting).

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Project directory organization and script naming conventions for research

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

figure

無料

Econometrics skill for generating publication-quality figures for top economics journals. Activates when the user asks about: "econometric figure", "publication figure", "journal figure", "AER figure", "QJE figure", "event study plot", "coefficient plot", "coefplot", "binned scatter", "binscatter", "RDD plot", "parallel trends plot", "kernel density", "distribution plot", "time series plot", "map", "figure formatting", "academic plot", "论文图表", "学术图", "系数图", "事件研究图", "散点图", "分布图", "趋势图", "回归可视化"

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新

Summarize academic papers, extract key findings, and identify research gaps

日本語の概要は準備中です。原文の説明を表示しています。

brycewang-stanford/Auto-Empirical-Research-Skills4,6612026年10月15日 更新