Skill UI

Guides researchers through drafting publication-ready machine learning papers for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM by combining expert writing philosophy with LaTeX templates, citation verification APIs, and collaborative workflows.

Generates publication-ready clinical decision support documents for pharma and clinical research, covering biomarker-stratified cohort analysis, evidence-graded treatment recommendations, statistical comparisons, and regulatory-ready LaTeX/PDF outputs.

Denario orchestrates a multi-agent AI to automate research workflows, covering idea generation, methodology development, computational experiments, and LaTeX publication output.

Guides researchers through creating conference-ready posters in LaTeX, covering layouts, visuals, AI-generated graphics, and overflow-safe design for academic communication.

Produces 50+-page market research dossiers with consulting-style LaTeX formatting, deep data lookups, strategic frameworks, and automated visual assets for investment and planning briefs.

Transforms LaTeX or PDF papers into interactive websites, narrated videos, and print-ready posters via the Paper2All pipeline, ideal for conference preparation, research promotion, and explorable academic showcases.

Provides Nano Banana Pro workflows for research talk slides, covering planning, slide generation, citations, and visual continuity for PowerPoint or LaTeX Beamer.

Generates concise 3-4 page LaTeX/PDF treatment plans across medical specialties, embedding SMART goals, evidence-based interventions, HIPAA-compliant formatting, and mandated AI-generated schematics for quick clinical actionability.

Provides LaTeX templates, formatting rules, and submission guidance covering journals (Nature, Science, PLOS, IEEE, ACM), conferences (NeurIPS, ICML, CVPR, CHI, etc.), posters, and grants so researchers can prepare compliant manuscripts efficiently.

This skill automates the complex and tedious process of porting academic papers written in LaTeX from one publisher's journal template (e.g., Springer) to another (e.g., MDPI, IEEE). It executes a structured multi-stage workflow, including content extraction, structural mapping, systematic fixing of common LaTeX issues (like float placement and math environments), and final compilation to ensure the output adheres to the target journal's specifications.

This skill autonomously polishes and improves generated scientific papers through multiple expert AI review cycles. It simulates a professional revision process: expert review (using GPT-5.4) → implementing structural and theoretical fixes → recompiling the LaTeX document. It is designed to enhance writing quality, address inconsistencies, refine claims, and improve overall presentation, making it ideal for post-draft academic polishing.

Automates the entire process of converting LaTeX source files into a professional, submission-ready PDF. This tool handles multi-pass compilation (using latexmk), diagnoses common LaTeX errors (such as missing packages, undefined references, and BibTeX syntax errors), and performs post-compilation checks, including page count verification according to specific academic guidelines (ICLR, IEEE, etc.). Ideal for researchers submitting papers.