review-qmd
Comprehensive single-file review. Generates preview with variables replaced, finds and replaces hardcoded values, adds _latex equations, validates consistency.
Browse published AI skills maintained by mikepsinn. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
10Repository stars across indexed skills
20Repository forks
0Average repository stars per indexed skill
2Repository stars may repeat across skills from the same repository.
Comprehensive single-file review. Generates preview with variables replaced, finds and replaces hardcoded values, adds _latex equations, validates consistency.
Validates parameters.py, checks for errors, and regenerates _variables.yml. Use when editing parameters, adding new values, or ensuring variable consistency.
Runs pre-render-validation.py and systematically fixes all detected errors. Use before rendering or committing to catch LaTeX, link, variable, citation, and import issues.
Checks QMD files for consistency, variable references, and cross-format links. Use after batch editing multiple files or before commits.
Finds and quantifies redundant content in QMD files - repeated equations, duplicate sections, similar paragraphs, and structural redundancy.
Critically analyze a calculated parameter for academic rigor. Checks methodology, identifies weaknesses, suggests improvements for economist audiences.
Systematically finds and replaces hardcoded numbers in QMD files with variables from _variables.yml. Use when auditing book for consistency.
Systematically find calculated variables that have corresponding _latex equations and add them where appropriate. Uses Ralph Loop for iterative processing.
Verifies claims have proper citations, searches for sources if needed, and adds them to references.bib. Use when making factual claims or adding statistics.
Manage academic paper publication workflows - track publication status across platforms (Zenodo, SSRN, arXiv, journals), generate PDFs, and update publication URLs in Quarto configs
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.