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.
9,461 skills from 277 repositories · updated 28 minutes ago
637 skills
- apsa-stylebrycewang-stanford/Auto-Empirical-Research-SkillsAPSA style checker for Quarto (.qmd) files. Checks numbers, capitalization, abbreviations, italics, in-text citations, titles of works, neutral and unbiased language, and APSA-specific terminology against the APSA Style Manual for Political Science (2018, updated 2023). Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to check APSA style, fix citations, review capitalization, check number formatting, or flag biased language in a .qmd document. For grammar, spelling, and punctuation, use the proofread skill instead. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.ScienceNo warnings★ 4.7K↓ —
- formula-derivationbrycewang-stanford/Auto-Empirical-Research-SkillsStructures and derives research formulas when the user wants to 推导公式, build a theory line, organize assumptions, turn scattered equations into a coherent derivation, or rewrite theory notes into a paper-ready formula document. Use when the derivation target is not yet fully fixed, the main object still needs to be chosen, or the user needs a coherent derivation package rather than a finished theorem proof.ScienceNo warnings★ 4.7K↓ —
- arxivbrycewang-stanford/Auto-Empirical-Research-SkillsSearch, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.ScienceNo warnings★ 4.7K↓ —
- paper-writingbrycewang-stanford/Auto-Empirical-Research-SkillsUse 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).ScienceNo warnings★ 4.7K↓ —
- reference-verifybrycewang-stanford/Auto-Empirical-Research-SkillsVerify references in an academic paper: check whether each BibTeX entry is real, whether in-text citations match the cited paper's actual content, and produce a structured verification report. Use when user says "验证参考文献", "ref verify", "check references", "核实引用", "引用是否正确", or wants to audit citations in a LaTeX manuscript.ScienceNo warnings★ 4.7K↓ —
- project-structurebrycewang-stanford/Auto-Empirical-Research-SkillsProject directory organization and script naming conventions for researchScienceNo warnings★ 4.7K↓ —
- aer-paper-bodybrycewang-stanford/Auto-Empirical-Research-SkillsUse when drafting or revising the body sections of an AER, AER:Insights, or AEJ manuscript — institutional background, data, empirical strategy, results, mechanisms, and conclusion. Covers equation conventions, results-paragraph narration, magnitude interpretation, and back-of-envelope policy calculations. Apply after the empirics are stable and before or alongside aer-introduction.ScienceNo warnings★ 4.7K↓ —
- paper-self-revisebrycewang-stanford/Auto-Empirical-Research-SkillsRevise an academic paper based on internal review comments. Reads review report or annotated manuscript, then applies revisions one by one with user approval. Trigger when user says "self revise" / "paper-selfrevise" / "内部修改" / "根据审稿意见修改".ScienceNo warnings★ 4.7K↓ —
- newprojectbrycewang-stanford/Auto-Empirical-Research-SkillsScaffold a new research project with standard directory structure, CLAUDE.md template, and documented README. Use this at the start of every new project to ensure consistent organization.ScienceNo warnings★ 4.7K↓ —
- aer-referee-simbrycewang-stanford/Auto-Empirical-Research-SkillsUse when a complete draft exists and needs an adversarial internal review before submission — simulating the AER desk screen and three referee reports with calibrated severity, scoring the paper against the editorial rubric, and producing a prioritized revise list. Apply after aer-consistency passes and before aer-submission; rerun until the simulated verdict is at least major R&R.ScienceNo warnings★ 4.7K↓ —
- stata-power-analysisbrycewang-stanford/Auto-Empirical-Research-SkillsPlan and critique power, MDE, and sample-size calculations for Stata-based research workflows. Use when the user is designing a study, checking detectability, or defending precision claims.ScienceNo warnings★ 4.7K↓ —
- academic-paper-verifybrycewang-stanford/Auto-Empirical-Research-SkillsThoroughly verify all code, tables, figures, modeling decisions, and quantitative claims in an academic paper against its source R scripts and output files. Use this skill whenever you need to audit, replicate, or verify an academic research paper - including cross-checking LaTeX tables against R output, validating econometric modeling choices, ensuring sample sizes are consistent, building a verification manifest, and running automated replication tests. Trigger this skill for any mention of: paper verification, replication check, table audit, code-paper consistency, reproducing results, verifying estimates, checking coefficients, or any variant of "does the paper match the code."ScienceNo warnings★ 4.7K↓ —
- paper-summarybrycewang-stanford/Auto-Empirical-Research-SkillsWrites expert academic paper summaries for social science research, particularly political science and applied statistics. Use when asked to summarize, review, or create a reading summary of an academic paper, PDF, or research article. Accepts a file (PDF or text format) or a directory of papers. Produces a structured markdown summary — approximately 400–600 words — covering primary contributions, major questions and answers with point estimates, methods and data, and limitations and robustness. Includes BibTeX citation retrieved from Google Scholar and keyword metadata.ScienceNo warnings★ 4.7K↓ —
- journal-selectionbrycewang-stanford/Auto-Empirical-Research-SkillsUse 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.ScienceNo warnings★ 4.7K↓ —
- assess-outlinebrycewang-stanford/Auto-Empirical-Research-SkillsAssesses a research paper outline (.qmd file) against structured criteria from Kosuke Imai's empirical research guide. Evaluates the abstract and section outline for: research question clarity, stated contributions, hypotheses and testable implications, data description, planned results and inferential approach, and robustness checks. Detects causal papers from the abstract and conditionally assesses identification strategy only when causal framing is present. Produces a structured markdown report with PASS/PARTIAL/FAIL assessments and actionable suggestions. Use when asked to assess, evaluate, review, or check a paper outline, abstract-and-outline, or research plan in a .qmd file.ScienceNo warnings★ 4.7K↓ —
- econfin-idea-finderbrycewang-stanford/Auto-Empirical-Research-Skills公司金融实证研究的"漏斗式选题查找器"。互动开场先后询问 (1) 研究方向、(2) 候选标题数量 N， 再扫描全球文献（已出版英文学术期刊 + SSRN working paper + 全球高校 department seminar 1 年内日程），基于 Edmans (2024) "1000 Rejections" 红线生成 N 个候选标题，**通过并行 subagent（Agent 工具）批量生成计划书 + 查新；每个 subagent 必须强制调用 Skill 工具加载 econfin-proposal 与 novelty-check 两个预设 skill 完成各自模块**，**只有当 novelty score >= 9 时（即 JF/JFE/RFS 顶刊层次），subagent 才把 proposal + 查新报告合并的 md 写入 F:\Dropbox\CC\选题大全\<研究方向短名>\（以"简短选题名称-分数"命名，子文件夹名由 Step 0 从用户输入的研究方向派生）；< 9 分的选题在 subagent 内部直接丢弃，绝不写盘、绝不输出**。当用户说"找选题"、"帮我找选题"、"想做 X 方向"、 "empirical CF idea search"、"批量生成研究计划书"、"100 ideas"、"econfin-idea-finder" 时触发。ScienceNo warnings★ 4.7K↓ —
- research-coordinatorbrycewang-stanford/Auto-Empirical-Research-SkillsResearch Coordinator v12.0 - Human-Centered Edition (Systematic Review Automation) Context-persistent platform with 24 specialized agents across 9 categories (A-G, I, X). Features: Human Checkpoints First, VS Methodology, Paradigm Detection, Systematic Review Automation. Supports quantitative, qualitative, mixed methods research, and systematic review automation. Language: English. Responds in Korean when user input is Korean. Triggers: research question, theoretical framework, hypothesis, literature review, meta-analysis, effect size, IRB, PRISMA, statistical analysis, sample size, bias, journal, peer review, conceptual framework, visualization, systematic review, qualitative, phenomenology, grounded theory, thematic analysis, mixed methods, interview, focus group, ethnography, action research, paper retrieval, AI screening, RAG builder, humanization, AI pattern detectionScienceNo warnings★ 4.7K↓ —
- literature-searchbrycewang-stanford/Auto-Empirical-Research-SkillsUse 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.ScienceNo warnings★ 4.7K↓ —
- paper-referee-revisebrycewang-stanford/Auto-Empirical-Research-SkillsRevise an academic paper based on journal referee reports. Reads referee comments from review report or annotated manuscript, then directly modifies main.tex one comment at a time with user approval. Generates response letter after revision. Trigger when user says "referee revise" / "paper-referee-revise" / "审稿意见修改" / "根据审稿人意见修改" / "referee report".ScienceNo warnings★ 4.7K↓ —
- causal-mlbrycewang-stanford/Auto-Empirical-Research-SkillsThis 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.ScienceNo warnings★ 4.7K↓ —
- citebrycewang-stanford/Auto-Empirical-Research-SkillsFinds a paper by title, author, or DOI, adds BibTeX to references.bib, and shows citation syntax. Use when adding a reference.ScienceNo warnings★ 4.7K↓ —
- initbrycewang-stanford/Auto-Empirical-Research-SkillsFills all [FILL:] placeholders across the template to initialize a new research project. Use when setting up a freshly cloned project.ScienceNo warnings★ 4.7K↓ —
- paper-planbrycewang-stanford/Auto-Empirical-Research-SkillsGenerate a structured paper outline from review conclusions and experiment results. Use when user says \"写大纲\", \"paper outline\", \"plan the paper\", \"论文规划\", or wants to create a paper plan before writing.ScienceNo warnings★ 4.7K↓ —
- fair-checkbrycewang-stanford/Auto-Empirical-Research-SkillsAudit manuscript and replication package against FAIR open-science principles.ScienceNo warnings★ 4.7K↓ —