Skill UI

Use the Recommendation Canvas to vet AI product concepts by mapping business and customer outcomes, hypotheses, positioning, risks, and success metrics so you can make defensible investment recommendations.

Generates structured peer-review quality critiques of academic papers, covering summaries, methodology scrutiny, contribution evaluation, literature positioning, and recommendations across domains whenever a user requests reviews, analyses, or summaries of research publications.

This skill provides authors with a comprehensive guide to positioning their computer science manuscript for the AAAI/ACM Conference on AI, Ethics, and Society (AIES). It covers critical aspects such as framing the contribution, meeting evidence standards, addressing social impacts, and distinguishing the work from similar venues like FAccT. Use it to refine submissions focused on AI ethics, governance, and socio-technical methods.

A comprehensive guide for positioning AI/ML manuscripts for top-tier general AI conferences like AAAI. It helps authors refine their scope, frame their contribution, provide necessary evidence (e.g., ablations, baselines), and strategically compare their work against related research and similar venues (ICML, IJCAI). Ideal for pre-submission manuscript refinement.

This guide provides comprehensive strategies for writing the Related Work section for submissions to AAAI. It teaches authors how to robustly position their paper's novelty by distinguishing contributions from both established archival literature and contemporaneous non-archival work (like arXiv papers). It also addresses specific reviewer expectations across various AI subfields (NeurIPS, ICML, ICLR) and outlines clear structural templates for maximum impact.

This guide helps authors audit the novelty and eligibility of multiagent system research for submission to AAMAS. It provides comprehensive advice on positioning the work against literature spanning multiple top-tier venues (e.g., NeurIPS, ICML, AAAI, EC, JAAMAS), integrating concepts from multiagent RL, game theory, and social choice. It ensures submissions are positioned accurately compared to the broader academic community, maximizing impact and minimizing rejection risk.

A comprehensive guide for NLP researchers on strategically positioning their work before writing. It teaches how to determine the core linguistic contribution, select the optimal academic venue (ACL, EMNLP, etc.), manage the scope (long vs. short papers), and align the research focus with specific conference themes and review expectations, maximizing publication impact.

A specialized guide for authors targeting the ACM Conference on Fairness, Accountability, and Transparency (FAccT). It helps authors strategically frame their responsible AI research, ensuring claims are rigorously grounded in both technical measurement and social context. Covers necessary evidence bars, scope calibration, and submission best practices for this niche venue.

This skill guides authors on positioning their manuscript for the ACM/IEEE International Conference on Human-Robot Interaction (HRI). It helps determine if the work fits the venue, how to re-frame the narrative, and what evidence (user studies, interaction contribution) is expected by HRI reviewers. Ideal for pre-submission strategy and scope calibration in human-robot interaction research.

This skill provides comprehensive strategic guidance for authors targeting ACM SIGGRAPH Asia. It helps assess a computer graphics manuscript's fit, required evidence (visualization, ablations, datasets), and structural positioning to meet the high novelty bar of this flagship venue. Use it for venue selection, manuscript re-framing, and developing a robust submission strategy against close competitors like SIGGRAPH or Eurographics.

A comprehensive guide for authors submitting papers to the ACL conference. It assists in positioning the manuscript, verifying topic fit (NLP, language models, semantics), and ensuring the evidence meets the high standards required for top-tier computational linguistics venues. Covers structure, best practices, and submission checklists.

This comprehensive guide helps computer vision researchers strategically position their work for the Asian Conference on Computer Vision (ACCV). It covers how to evaluate manuscript fit, restructure the narrative from general to conference-specific, optimize evidence presentation (including ablations and failure modes), and understand ACCV's regional niche compared to global flagships like CVPR or ECCV.