Skill UI

Provides a comprehensive, detailed audit checklist for authors submitting papers intended for NAACL. This guide walks through the complex ACL Rolling Review (ARR) submission cycle, ensuring the manuscript passes all mandatory technical gates—such as anonymity checks, format compliance, structural requirements, and accurate declaration—before the final conference commitment. Essential for navigating the unique timeline and rigorous standards of top NLP conferences.

A comprehensive guide for NLP researchers to determine the ideal conference venue (NAACL, ACL, EMNLP, etc.) for their paper. It analyzes timing, target audience fit, and the unique regional focus of NAACL (Nations of the Americas) to ensure the work is submitted to the most appropriate and receptive community.

This skill serves as a detailed guide for authors submitting theoretical articles in syntax or morphology to Natural Language & Linguistic Theory (NLLT). It outlines the journal's specific expectations, emphasizing that formal analyses must be deeply grounded and rigorously tested using rich, representative, and often cross-linguistic empirical data. Use this tool to assess the methodological rigor, scope fit, and structural requirements of your manuscript against NLLT's high academic standards.

A comprehensive guide for authors targeting Nature Machine Intelligence. It outlines the high standard required for AI/ML research, emphasizing conceptual significance, real-world impact, interdisciplinary relevance, and rigorous ethical and methodological depth. Use this tool to assess fit and framework your submission for a Nature-family audience.

This skill provides a comprehensive framework for authors targeting top-tier AI conferences like NeurIPS. It guides researchers in refining their manuscript's narrative, ensuring the contribution meets the venue's standards for broad, high-novelty machine learning research. It covers topic fit, evidence bar requirements, structuring the argument, handling interdisciplinary claims, and navigating the specific submission cycle rules for maximizing acceptance chances.

Provides comprehensive guidelines for packaging and presenting research artifacts (code, data, models, benchmarks) submitted to NeurIPS. It details requirements for anonymous review packages, public release, and ensures scientific claims are reproducible by providing necessary metadata, licenses, and execution details.

This skill guides authors on how to strategically position their machine learning research against complex academic landscapes. It covers comparing work to neighboring conferences (ICML, ICLR), analyzing contemporaneous preprints, and defining the exact technical delta from prior methods to minimize novelty risk for top-tier AI venues.

This skill simulates the rigorous peer review process used in top-tier AI and machine learning conferences (like NeurIPS). It helps users diagnose potential weaknesses in a submission regarding quality, clarity, significance, ethical compliance, and reproducibility. It guides the identification of decision-relevant issues that ACs and reviewers are likely to raise, helping authors strategically plan responses for revision.

This skill guides researchers through the rigorous validation process of their AI/ML paper for NeurIPS. It helps determine if the core contribution is robust enough for the main track, suggests the most appropriate NeurIPS track (e.g., E&D, Position), and refines the contribution type (Theory, Use-Inspired, etc.) to maximize the chances of acceptance.

A comprehensive guide for refining machine learning research papers tailored for NeurIPS submission. It teaches how to structure introductions, calibrate claims with evidence, explicitly state limitations, and address mandatory academic checklist items (e.g., reproducibility, broader impact). Use this skill to transform technical writing into a reviewer-proof, high-impact academic manuscript.

A comprehensive guide for authors targeting the NAACL conference. It helps strategize the fit, framing, and rigor required for NLP and Computational Linguistics manuscripts. Use this to structure your paper, understand the evidence bar, and position your work for a top-tier conference audience.

This plugin integrates the OpenViking context database, providing powerful long-term memory, session archiving, and semantic recall for OpenClaw agents. It enables agents to query, debug, and manage persistent knowledge bases, significantly enhancing conversational depth and complex tool usage.