All Skills

Use when aer-identification has fixed the design, after methodology choice and before aer-robustness or aer-tables-figures, to run an AER-track analysis with StatsPAI — the agent-native Python engine and MCP server for causal inference, robustness, sensitivity, and publication-ready table export.

Use when a research implementation plan exists in docs/superpapers/plans/ and the user is ready to execute it — collecting data, running analysis, producing outputs, writing the paper. Orchestrates task execution with replication-driven verification and two-stage review at phase boundaries.

Use when a paper is complete or near-complete and a holistic pre-submission audit is needed. Cross-cuts text, code, tables, figures, results, citations, and reproducibility in a single pass and produces a persistent audit report. Works standalone on papers written outside the plugin.

Run replication, robustness, and specification-sensitivity workflows for Stata projects. Use when a researcher wants to reproduce a result, rerun a pipeline, compare specifications, audit a do-file sequence, or check whether a claim is stable.

Systematic audit and review by Referee 2. Two modes — "deck" reviews slide presentations for rhetoric, visual quality, and compile cleanliness; "code" performs cross-language replication and econometric audit of empirical pipelines. Use when reviewing slides, auditing code, or verifying replication.

APSA 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.

Prose quality checker for Quarto (.qmd) files, grounded in William Zinsser's *On Writing Well* (30th Anniversary Edition). Checks for clutter, weak verbs, hollow qualifiers, clichés, inflated academic voice, poor leads and endings, pronoun and tense inconsistency, and unclear explanation. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to improve prose quality, tighten writing, reduce clutter, or apply Zinsser's writing principles to a draft. For grammar and punctuation, use the proofread skill. For APSA style rules, use the apsa-style skill. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.

Monitor running experiments, check progress, collect results. Use when user says "check results", "is it done", "monitor", or wants experiment output.

Generate publication-quality AI illustrations for academic papers using Gemini image generation. Creates architecture diagrams, method illustrations with Claude-supervised iterative refinement loop. Use when user says "生成图表", "画架构图", "AI绘图", "paper illustration", "generate diagram", or needs visual figures for papers.

Patterns for Bayesian inference in R using brms, including multilevel models, DAG validation, and marginal effects. Use when performing Bayesian analysis.

金融经济学实证论文计划书生成器。根据用户提供的研究方向，生成包含标题、假说、数据来源、实证策略、 预期结果表格、稳健性检验、异质性分析、机制检验等12个完整模块的研究计划书。 内置中国微观/宏观数据库（皮皮侠1599个数据集、马克数据377个数据集）和WRDS国际数据库索引， 自动匹配可用数据源。融合Edmans (2024) "Learnings From 1000 Rejections"的编辑视角作为质量护栏， 确保选题具有真正的边际贡献而非"just another determinant of Y"。 当用户提到以下任何情境时触发：写研究计划书、research proposal、论文开题、选题+计划、 帮我设计一个实证研究、empirical research design、我想研究X对Y的影响怎么做、 帮我找个能发表的选题、generate proposal、写一个可以投稿的研究方案、 研究设计、identification strategy、DID/RDD/IV研究设计。 即使用户只是描述了一个经济金融现象并想知道"能不能做成论文"，也应考虑使用此技能。

根据研究者提供的**研究计划书（Research Proposal）**执行基于**外国（美国/欧盟/英国/日本/跨国）制度环境**的公司金融类实证研究全流程。**启动后第一件事：根据计划书的主题、识别策略、贡献边际与样本范围，从外国 CF 顶刊池（AER/QJE/JPE/JF/JFE/RFS/JFQA/JAR/JAE/MS/JCF/JBF 等 25+ 期刊）中推荐 5 本最匹配的目标期刊（[J1]–[J5]），等待研究者明确选定一本；该期刊决定 main.tex 的 bibliographystyle、Section 骨架、Introduction 风格与表注规范**。然后用 Python 完成数据清洗、描述性统计、基准回归、内生性检验（IV/2SLS、DML）、平行趋势、异质性、机制、稳健性检验与图表绘制。LaTeX 表格和图像严格遵循 template/ 示例格式，研究逻辑与排版严格遵循 rule/ 下的《通用实证研究逻辑与规范总结》与《回归表写作规范总结》。数据集与政策集从 asset/ 中按计划书中的关键词检索（WRDS / NBER/Fed releases / FRED / 全球宏观库）。**当计划书预期的实证结果无法实现时（系数不显著、平行趋势不通过、IV 弱工具、机制不成立等），skill 自动切换备选方案直至完成研究项目**。最终交付物：Python 代码 + LaTeX 表格 + 图像（.pdf/.png）。触发条件：研究者提交研究计划书（含 X→Y 假设、识别策略、样本、政策冲击等）。

Evaluate a paper's contribution novelty, identify best-fit SSCI journal fields and ABS star rating, and recommend 20 target journals. Trigger when user says "paper submission" / "paper-submission" / "投稿评估" / "期刊推荐" / "target journal" / "选刊".

Introduction to literature search & review skills - systematic paper finding, screening, extraction, and citation traversal

Download, split, and deeply read academic PDFs. Use when asked to read, review, or summarize an academic paper. Splits PDFs into 4-page chunks, reads them in small batches, and produces structured reading notes — avoiding context window crashes and shallow comprehension.

Activate when the user is drafting any academic economics content from scratch (e.g., outlines, abstracts, introductions, data/methods/identification sections, results narratives, conclusions, referee responses, table/figure captions) and needs economics-specific structure, phrasing options, and quality checks to produce publication-ready prose.

Extract clean markdown content from web pages using Defuddle CLI, removing clutter and navigation to save tokens. Use instead of WebFetch when the user provides a URL to read or analyze, for online documentation, articles, blog posts, or any standard web page.

Use 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.

Use 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.

Design and format publication-quality tables: column order, row grouping, notes, precision, reproducibility.

Public finances briefing. Supports UK, US, and Australia. Produces a single compact briefing on borrowing, debt, receipts, spending, and fiscal rules. Optional debt sustainability analysis via the debtkit R package. User-selectable sub-components and multi-format export.

Industry and market research. Market sizing, structure, competition, regulation, supply chains, pricing, M&A. Produces a single compact, source-cited research report with Porter's Five Forces, HHI / CR4, PESTLE, and trade flows. Supports UK, US, EU, Australia, and global scope, with multi-geography comparison.

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"

Find free legal full-text versions of scholarly articles via Unpaywall

Scaffold 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.

Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".

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。

Expert jq usage for JSON querying, filtering, transformation, and pipeline integration. Practical patterns for real shell workflows.

Centralized 'Truth Engine' for cross-jurisdictional legal context (US, EU, CA) and contract scaffolding.

Dynamic multi-agent workflows — plan first, then orchestrate parallel agents with adversarial verification via the local odw daemon. Use when the user asks for a "workflow", says "ultracode", or hands you a task spanning many files/items that benefits from parallel agents.

Run a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO. Use as the umbrella skill when the user asks for a full SEO analysis or strategy.

Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.

Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.

Control cmux workspaces, panes, surfaces, and agent sessions safely from macOS terminal workflows.

Anti-over-engineering guardrail that activates when an AI coding agent expands scope, adds abstractions, or changes files the user did not request.

Runs repeatable AI work as checked, budgeted workflow files.