Skill UI

This skill provides comprehensive data handling capabilities specifically for the Guidewire platform. It covers robust entity management (CRUD operations using Gosu), complex data migration using ETL tools and batch processing, and advanced data governance practices. Key features include implementing GDPR data purge rules and anonymization techniques for secure testing environments. Ideal for developers managing core insurance platform data.

This advanced engine acts as the memory layer for C-suite advisory sessions. It loads, manages, and enriches detailed company context from local files, automatically detecting context staleness. Crucially, it enforces strict anonymization protocols before any external API calls, ensuring sensitive data (like revenue or names) is protected while providing deep, specific insights for high-level business strategy.

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.

A comprehensive guide for preparing accepted research papers for final submission to major conferences (e.g., AAAI Press). This process covers strict template adherence, deanonymization of author details, managing copyright transfer, optimizing page counts (including purchasing extra technical pages), and ensuring all source files (LaTeX/Word, figures, bibliography) are correctly formatted for professional publication.

A comprehensive guide for authors transitioning an accepted, anonymous conference submission into the final, public camera-ready version for publication. It covers de-anonymization steps, including restoring author details, updating proceedings metadata, reflowing figures for multiagent papers, and integrating rebuttal promises without expanding the core contribution. This ensures adherence to strict publishing standards.

A comprehensive guide for packaging and submitting evidence packages (artifacts) for NLP research papers, such as code, datasets, prompts, and model outputs. It details requirements for reproducibility, adhering to the Responsible NLP checklist, ensuring proper anonymization, and preparing for post-acceptance public release in academic settings like ACL.

This comprehensive guide outlines the meticulous workflow for preparing a research paper for final publication (Camera-Ready) after acceptance at major NLP conferences like ACL. It covers critical steps including de-anonymization (restoring author details and acknowledgements), integrating mandates from meta-reviews, adding required disclosures (e.g., funding, AI assistance), and ensuring all technical metadata, font embedding, and licensing comply with the permanent open-access standards of the ACL Anthology.

This comprehensive guide details the essential steps required to transition an accepted, anonymous conference paper into the final, public 'camera-ready' version for major academic publications like ACM MM. It covers de-anonymization, completing ACM eRights forms, incorporating CCS concepts, releasing permanent code/data artifacts, and preparing for the final presentation.

A comprehensive guide for researchers in electronics and signal processing preparing submissions to Acta Electronica Sinica (AES). It outlines best practices for proactively structuring, documenting, and disclosing research artifacts—including code, datasets, and hardware designs—to maximize the paper's credibility and chances of acceptance, even without mandatory journal badges. Covers anonymization, reproducibility standards, and proper disclosure in the manuscript.

A comprehensive final preflight guide for submitting manuscripts to the American Journal of Political Science (AJPS) via Editorial Manager. It covers strict requirements for double-blind review, including anonymization rules, word count limits, formatting (APSA/Chicago), Supporting Information caps, and human subjects documentation, ensuring the manuscript is ready before hitting submit.

This comprehensive preflight checklist guides authors through the rigorous submission process for the Academy of Management Journal (AMJ). It covers crucial details such as double-blind anonymization, AOM house-style formatting (Times New Roman 12pt, double-spaced), ethical declarations (AI disclosure, IRB), and adherence to the ScholarOne portal requirements. Use this guide before finalizing your submission.

A comprehensive preflight checklist designed for authors submitting manuscripts to the Accounting, Organizations and Society (AOS) journal via Editorial Manager. It verifies all necessary components, including double-anonymization compliance, declarations (AI, ethics, interests), article types, and open-access decisions, ensuring readiness before the final submission.