Skill UI

Automates Open Graph metadata guidance for frontend workflows, offering best practices, React/Vue/CSS tips, and ready-to-apply code.

This meta-skill helps discover and apply the right engineering workflow skill for your current task. It organizes skills by development phase and guides you through processes like planning, implementation, testing, and deployment. It enforces core behaviors like surfacing assumptions, managing confusion, and verifying work to prevent common engineering mistakes and ensure quality.

PDFtk Server is a powerful command-line tool designed for comprehensive manipulation and processing of PDF documents. It allows users to programmatically merge, split, rotate, secure (encrypt/decrypt), fill forms, apply watermarks, extract metadata, repair corrupted files, and much more. Ideal for automation scripts, batch processing, and any scenario requiring robust, scripted PDF handling from the terminal.

This privileged skill lands self-modification patches approved by users after /meta-optimize. It enforces a privilege boundary by acting as the only skill permitted to mutate the skill corpus. It runs a fresh cross-model jury at landing time to verify patches before applying changes, ensuring safety and preventing self-modification loops. Requires explicit human invocation.

A comprehensive guide detailing the transition of an accepted FSE paper into a journal-ready (PACMSE) camera-ready format. This process involves critical steps including full de-anonymization, applying the final ACM template, completing detailed journal metadata (ORCID, CCS), integrating required revisions, and permanentizing open science artifacts with DOIs.

A comprehensive guide for polishing academic manuscripts intended for the Journal of Economic Growth (JEG). It instructs authors on structuring arguments around core growth mechanisms, translating raw econometric coefficients into meaningful growth language (e.g., convergence, productivity), and applying specific metadata and citation standards (APA, JEL codes) required by top-tier journals in development economics.

A comprehensive guide for authors preparing accepted academic papers for publication in the ACM Digital Library. This process covers de-anonymization (restoring author details, funding, and public links), applying the strict double-column format, adhering to page budgets, incorporating all results promised during the rebuttal, and finalizing necessary metadata and conference artifacts.

This guide provides comprehensive steps for preparing a camera-ready version of an accepted academic conference paper, such as those for the PACMMOD PODS track. It covers essential tasks including complete de-anonymization, applying final journal formatting, integrating required revisions, populating detailed metadata (ORCID, DOI, CCS concepts), and ensuring the full version is correctly posted and cross-linked on arXiv.

This comprehensive guide details the mandatory production steps required after a research paper is accepted for publication in Springer LNCS. Key tasks include de-anonymizing the manuscript (restoring true names, affiliations, and funding details), applying the specific llncs.cls format, finalizing metadata with ORCIDs, integrating reviewer feedback, permanently linking artifacts using DOIs, and completing the CC-BY open-access licensing forms.

A comprehensive checklist for authors preparing an accepted IEEE VIS paper for the final camera-ready journal submission (IEEE TVCG). It guides authors through critical steps including de-anonymizing the work, applying the correct journal template, completing comprehensive metadata (ORCID, DOI), integrating required revisions, and ensuring all open materials are permanently linked to public archival DOIs.

An internal, deterministic runtime for structured scholarly writing workflows (meta-paper-write). It processes JSON input to perform critical operations such as persisting sections, assembling LaTeX manuscripts, compiling PDFs using xelatex/bibtex, managing citations, and applying length expansions. It ensures artifact integrity and high-quality output for academic publications.

Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics. It also covers creating and uploading datasets, and uploading agent traces.