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.
14,533 skills from 417 repositories · updated 16 hours ago
2,021 skills
- helpbrycewang-stanford/Auto-Empirical-Research-SkillsDiverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말OtherNo warnings★ 4.7K↓ —
- doctorbrycewang-stanford/Auto-Empirical-Research-SkillsSystem diagnostics and health checks for Diverga plugin. OpenClaw-style Check-Report-Fix pattern with 5-layer diagnostics. Triggers: /diverga:doctor, diverga doctor, system check, diagnose, 진단OtherNo warnings★ 4.7K↓ —
- vast-gpubrycewang-stanford/Auto-Empirical-Research-SkillsRent, manage, and destroy GPU instances on vast.ai. Use when user says "rent gpu", "vast.ai", "rent a server", "cloud gpu", or needs on-demand GPU without owning hardware.OtherNo warnings★ 4.7K↓ —
- figurebrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics 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"OtherNo warnings★ 4.7K↓ —
- data-docbrycewang-stanford/Auto-Empirical-Research-SkillsDocument datasets, variables, sources, and merge keys for replicationOtherNo warnings★ 4.7K↓ —
- stata-helpbrycewang-stanford/Auto-Empirical-Research-SkillsLook up Stata command documentation and display formatted help text.OtherNo warnings★ 4.7K↓ —
- stata-lintbrycewang-stanford/Auto-Empirical-Research-SkillsRun static analysis on a Stata .do or .ado file and report style and best-practice issues.OtherNo warnings★ 4.7K↓ —
- ml-causalbrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics 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"OtherNo warnings★ 4.7K↓ —
- web-accessbrycewang-stanford/Auto-Empirical-Research-Skills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。OtherNo warnings★ 4.7K↓ —
- feishu-notifybrycewang-stanford/Auto-Empirical-Research-SkillsSend notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.OtherNo warnings★ 4.7K↓ —
- stata-resultsbrycewang-stanford/Auto-Empirical-Research-SkillsFetch and display stored r(), e(), and s() results from the last Stata command.OtherNo warnings★ 4.7K↓ —
- deepstream-run-mv3dtNVIDIA/skillsRun and operate the DeepStream Multi-View 3D Tracking reference app, also known as MV3DT. Use when the user asks to set up prerequisites, run shipped MV3DT samples, run Multi-View 3D Tracking on custom synchronized MP4 datasets, import camera calibration, delegate missing calibration to AutoMagicCalib, inspect OSD or BEV visualization, consume MV3DT Kafka metadata, or clean up MV3DT run state in the DeepStream MV3DT app directory.OtherNo warnings★ 3.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —
- liangziwei-skillmomozi1996/awesome-ai-persona-skills量子位(QbitAI,国内AI行业Top 1科技媒体)的AI科技自媒体创作思维——团队出品·数据驱动·速报+深析+智库三位一体。 触发词:「量子位视角」「像量子位那样写」「AI行业新闻快讯」「AI十大趋势」「AIGC全景图谱」「MEET智能未来」。 擅长:AI行业新闻快讯、深度特稿报道、产业研究报告(AI十大趋势/AIGC全景图谱)、年度大会内容框架、 行业人物深度专访、数据驱动新闻、短快讯50+条密集型更新。OtherNo warnings★ 987↓ —
- referee-responsebrycewang-stanford/Auto-Empirical-Research-SkillsStructure responses to referee reports for R&R submissionsOtherNo warnings★ 4.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —
- 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★ 4.7K↓ —