What problem does it solve? Writing a publication-ready ML/AI paper involves coordinating literature review, experiment design, statistical analysis, LaTeX drafting, citation verification, and venue-specific formatting — a process where missed steps (hallucinated citations, missing checklists, weak baselines) cause desk rejections. ## Core Features & Use Cases - Full Research Lifecycle: Eight iterative phases covering project setup, literature review, experiment design, execution monitoring, statistical analysis, drafting, self-review, and submission for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM. - Citation Verification Workflow: Programmatic BibTeX retrieval via Semantic Scholar, CrossRef, and arXiv APIs with a mandatory 5-step verification process to prevent hallucinated references. - Venue Templates & Checklists: Official LaTeX templates for six conferences plus pre-submission checklists covering page limits, reproducibility statements, and ethics requirements. - Use Case: A researcher with experimental results asks the agent to draft an ICML submission — the skill produces a grounded draft from the experiment log, verifies every citation via DOI content negotiation, applies the ICML 2026 template, and runs a simulated reviewer pass before submission. ## Quick Start Use the research-paper-writing skill to draft a NeurIPS paper from the experiment results in my results/ directory, with verified citations and the official template.