Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
26,393 skills from 995 repositories · updated 20 minutes ago
5,925 skills
- council0xNyk/council-of-high-intelligenceConvene the Council of High Intelligence — multi-persona deliberation with historical thinkers for deeper analysis of complex problems.OtherNo warnings★ 4.7K↓ —
- kaggle-learnerbrycewang-stanford/Auto-Empirical-Research-SkillsThis skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.OtherNo warnings★ 4.8K↓ —
- submitbrycewang-stanford/Auto-Empirical-Research-SkillsSubmission pipeline — journal targeting, replication package, audit, and final gate. Replaces /submit, /target-journal, /audit-replication, /data-deposit.OtherNo warnings★ 4.8K↓ —
- revisebrycewang-stanford/Auto-Empirical-Research-SkillsR&R cycle — classify referee comments and route to appropriate agents. Replaces /respond-to-referee.OtherNo warnings★ 4.8K↓ —
- replicatebrycewang-stanford/Auto-Empirical-Research-SkillsBuild and verify replication packages — routes to reproducibility-auditor agentOtherNo warnings★ 4.8K↓ —
- grillmebrycewang-stanford/Auto-Empirical-Research-Skills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OtherNo warnings★ 4.8K↓ —
- stata-referee-responsebrycewang-stanford/Auto-Empirical-Research-SkillsOrganize and execute Stata workflows for referee responses, robustness requests, and coauthor follow-ups. Use when the user needs to answer a critique with targeted reruns, tables, figures, and a defensible audit trail.OtherNo warnings★ 4.8K↓ —
- talkbrycewang-stanford/Auto-Empirical-Research-SkillsCreate and audit presentations (Beamer or Quarto RevealJS). Combines talk creation, visual audit, and compilation. Replaces /create-talk, /visual-audit, /compile-latex (for talks).OtherNo warnings★ 4.8K↓ —
- Significance-Searchbrycewang-stanford/Auto-Empirical-Research-SkillsParallel control variable combination search via Stata. Exhaustively searches all subsets of optional controls to find the combination that maximises |t| of the independent variable. Activates when user says: "控制变量搜索", "搜控制变量", "control variable search", "跑控制变量组合", "暴力搜索", "调控制变量".OtherNo warnings★ 4.8K↓ —
- stata-data-provenancebrycewang-stanford/Auto-Empirical-Research-SkillsTrack dataset lineage, transformation steps, merge logic, and reproducibility risks in Stata workflows. Use when the user needs to explain where data came from, how it changed, or why a pipeline can be trusted.OtherNo warnings★ 4.8K↓ —
- new-projectjmagly/aiwgScaffold a new AIWG-managed project with .aiwg/ directory structure, starter CLAUDE.md, and framework registry. Use when creating or scaffolding a new project.OtherNo warnings★ 225↓ —
- aer-submissionbrycewang-stanford/Auto-Empirical-Research-SkillsUse 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.OtherNo warnings★ 4.8K↓ —
- aer-literaturebrycewang-stanford/Auto-Empirical-Research-SkillsUse 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 published version. Apply at topic selection for the novelty scan and again before drafting the introduction.OtherNo warnings★ 4.8K↓ —
- agent-loopjmagly/aiwgDetect requests for iterative autonomous agent loops and route to the appropriate loop executorOtherNo warnings★ 225↓ —
- r-bayesbrycewang-stanford/Auto-Empirical-Research-SkillsPatterns for Bayesian inference in R using brms, including multilevel models, DAG validation, and marginal effects. Use when performing Bayesian analysis.OtherNo warnings★ 4.8K↓ —
- monitor-experimentbrycewang-stanford/Auto-Empirical-Research-SkillsMonitor running experiments, check progress, collect results. Use when user says "check results", "is it done", "monitor", or wants experiment output.OtherNo warnings★ 4.8K↓ —
- fletcherbrycewang-stanford/Auto-Empirical-Research-SkillsDefamiliarization audit for empirical output. Systematically interrogates every feature of a figure, table, or set of results — not just the main finding. Named for Jason Fletcher, who asked about the spike at t=1 when everyone else was looking at t=2. Use when you have output and are about to interpret or report it.OtherNo warnings★ 4.8K↓ —
- referee-responsebrycewang-stanford/Auto-Empirical-Research-SkillsStructure responses to referee reports for R&R submissionsOtherNo warnings★ 4.8K↓ —
- ols-regressionbrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics 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"OtherNo warnings★ 4.8K↓ —
- r-oopbrycewang-stanford/Auto-Empirical-Research-SkillsR object-oriented programming guide for S7, S3, S4, and vctrs. Use when designing R classes or choosing an OOP system.OtherNo warnings★ 4.8K↓ —
- analyze-resultsbrycewang-stanford/Auto-Empirical-Research-SkillsAnalyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.OtherNo warnings★ 4.8K↓ —
- did-analysisbrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics 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"OtherNo warnings★ 4.8K↓ —
- training-checkbrycewang-stanford/Auto-Empirical-Research-SkillsPeriodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.OtherNo warnings★ 4.8K↓ —
- stata-resultsbrycewang-stanford/Auto-Empirical-Research-SkillsFetch and display stored r(), e(), and s() results from the last Stata command.OtherNo warnings★ 4.8K↓ —