Adversarially audit changed analysis code against a base ref, hunting for correctness errors in sample construction, merges, variable construction, silent failures, and clustering or fixed effects. Runs in an isolated subagent. Use before circulating results or submitting. This is not a reproducibility or paper-to-code review — use review-paper-code for that.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Explain a code change as a standalone offline HTML page with a five-question quiz. Reads the diff and the surrounding code from scratch, states the consequences for the empirical results, and saves the page outside the repository under a dated filename.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Build a LaTeX beamer slide deck in the explorable-explanation style (Nicky Case) — one idea per frame, assertion titles, a concrete running example, TikZ/pgfplots stages the presenter steps through, the source's own figures recoloured into the deck palette, an appendix of side rooms, and a screenshot-and-log check of every page. Use for any request for a Beamer, LaTeX or TeX presentation, talk, slides, seminar, conference, lecture, keynote or job-market deck, "turn this paper into beamer slides", a deck that must be a PDF, or for revising or reviewing a deck built this way. The sibling skill explorable-deck builds the same deck in Quarto reveal.js; use this one when the user names Beamer, LaTeX, TeX or PDF, or works in a LaTeX project. Not for a website explorable (that is explorable-explanations) or a poster.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Build a Quarto reveal.js slide deck in the explorable-explanation style (Nicky Case) — one idea per slide, assertion titles, a concrete running example, run-time SVG stages the presenter drives live, the source's own figures recoloured into the deck palette, and an appendix of side rooms. Use for any request for a presentation, talk, slides, a seminar, conference, lecture, keynote or job-market deck, a Quarto or reveal.js deck, "turn this paper into slides", "a deck like the explorable", or for revising or reviewing a deck built this way. Prefer it over .pptx skills unless the user names PowerPoint, Beamer, LaTeX or Google Slides. Not for a website explorable (that is explorable-explanations) or a poster.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Convert a LaTeX research paper into a policy brief, 1-page summary, or 5-page summary for a general audience, with factual review and a standalone HTML page for GitHub Pages.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Split a PDF into chunks and convert it to readable markdown text. Use when the user wants to read, extract, or convert a PDF document.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Run a 6-agent pre-submission panel review for a grant proposal targeting a specified funder or program
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Run a fast 3-agent mechanical check of an economics paper — spelling and grammar, internal consistency and cross-references, and unsupported claims. Reports fixable errors, not editorial judgment.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Run a 6-agent pre-submission review of a pre-analysis plan (PAP) for a specified registration target or journal
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Run an 8-agent pre-submission referee report for an academic paper targeting a specified journal
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Review research code for reproducibility and quality, extract the paper's main empirical claims, compare paper to code, and write a constructive markdown report. Designed for social science / economics projects with LaTeX papers and Stata, R, or Python code.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新
Run a fast 2-agent pre-submission check for an economics paper — focuses on contribution, identification, and causal overclaiming. Completes in ~1 minute.
中文简介正在准备中。当前显示原文说明。
claesbackman/AI-research-feedback☆ 5072026年10月24日 更新