1.3K skills · sorted by relevance
Create paper figures and LaTeX comparison tables from experiment data in JSON or CSV files. Save reproducible plotting scripts, use consistent styling, and check rendered figures for readability, fair comparisons, and captions supported by the data.
Create consistent paper figures and comparison tables from experiment data. The skill selects suitable chart types, saves reusable plotting scripts, prepares LaTeX insertion code, and checks rendered figures for readability and comparisons for consistency with the underlying data.
Read, create, and organize PDF files, including merging documents, splitting pages, extracting tables, and filling forms. It also covers password protection and OCR, which recognizes text in scanned pages for extraction or search.
Clean, combine, summarize, and reshape tabular data with pandas DataFrames, Python's table-like data structures. Produces transformation code and validation checks, including time series processing and memory-conscious approaches for large datasets.
Extract text, tables, and images from PDFs, or create and modify PDF documents. Covers merging, splitting, rotation, watermarks, password protection, page rendering, and OCR, which turns scanned page images into text.
Build reusable Convex backend components with their own database tables and a small API, the functions an app calls. It guides component structure, app integration, authentication boundaries, and checks for generated code and type errors.
Maintain data retention in ClawHub's Convex tables by classifying each table, defining expiration fields, and bounding cleanup jobs. Guide changes to temporary data and expired authentication records, with focused tests and runtime verification.
Extract text from images and PDFs, including handwriting, tables, invoices, and receipts. Return plain text, Markdown tables, or structured JSON fields, with options to select a recognition provider and specific PDF pages.
Generate PDF checklists, reports, and assessments with sections, tables, and scoring criteria using Python. Choose a suitable library, save the document for download, and check the output, with shell execution as an alternative when the sandbox fails.
Draft and revise machine learning, computer vision, and natural language processing papers. Improve section structure, paragraph flow, and figures or tables, then check major claims against experimental evidence and review the draft from a skeptical reviewer’s perspective.
Extract text, tables, and images from PDFs, create documents, combine or split files, and fill forms. It also covers OCR, which reads text from scanned pages, plus watermarks, page rotation, and password protection.
Format Obsidian notes, repair internal links, and create registry tables and canvas diagrams. The skill handles formatting and derived files while leaving decisions about where knowledge belongs outside its scope.
Extract text, tables, and images from PDFs, combine or split documents, rotate pages, fill forms, and create new files. It also covers password protection and OCR, which recognizes text in scanned pages for searching and reuse.
Write and review R analysis scripts for a sewage research project using its established conventions. Estimate requested regression models, add specifications, and save LaTeX tables, figures, and model objects for use in the research paper.
Turn regression results, summary statistics, and simulation output into tables and figures for academic papers. Apply consistent number formatting, labels, and accessible visual styles, then produce files ready to include in LaTeX documents.
Analyze U.S. electoral district plans in R with redistverse. Guides data preparation, simulations under population and geographic constraints, diagnostic checks, and comparisons of district shape, partisan fairness, and administrative splits through maps and summary tables.
Analyze datasets in R or Python, from exploring distributions and missing values to fitting regressions. Produce tables and figures for publication, save scripts and model results, and review the analysis for common problems.
Create summary tables, treatment and control comparisons, and correlation matrices using Python, R, or Stata. Summarize averages, variation, sample sizes, and missing data to understand a dataset before regression or prepare tables for a research paper.
Prepare benefits and costs tables for a project before a cost-benefit analysis. Each item includes importance, sponsor cash flow, a measurement approach, and a monetary valuation method, using one of five supported appraisal frameworks.
Check an academic paper’s tables, numerical claims, and modeling choices against R scripts and outputs. Produce discrepancy reports, a record linking claims to code, and automated tests that rerun the analysis.
Build a reproducible Stata analysis from data cleaning through modeling, diagnostic checks, and robustness tests. Generate runnable .do files, regression tables, and figures for empirical papers, with additional workflows for epidemiology and machine learning approaches to causal inference.
Work with PDFs to extract text, tables, and images, combine or split documents, rotate pages, and create new files. The guide also covers forms, watermarks, password protection, and OCR, which recognizes text in scanned pages.
Present comparisons, trends, and progress as interactive cards, tables, and charts inside Codeg chat. Create layouts with tabs, checklists, and simple forms that update displayed state and validate user input.
Read, create, and edit .docx documents with python-docx, then render pages for visual inspection. Organize headings, tables, and lists, and check spacing, alignment, pagination, and readability before delivering the finished document.