Skill UI

A comprehensive tool for publishing fully optimized blog content to major CMS platforms like WordPress or Webflow. It enforces multiple quality gates, including SEO optimization, brand voice alignment, content scoring, and compliance checks, ensuring drafts are ready for live deployment with scheduling and metadata.

A comprehensive tool for creating, validating, and deploying targeted email marketing campaigns across major platforms (SendGrid, Klaviyo, Customer.io, etc.). It manages the entire campaign lifecycle, from content personalization and A/B testing setup to rigorous spam scoring, compliance checks, and optimal send time scheduling, ensuring maximum deliverability and brand consistency.

Intelligently translates marketing content across multiple languages, automatically selecting the optimal service (DeepL, Sarvam AI, Google Cloud, etc.). It goes beyond literal translation by performing transcreation analysis for cultural nuances, humor, and emotional impact, ensuring brand voice and marketing effectiveness are preserved globally. The process includes quality scoring and adherence to specific compliance rules and glossaries.

This skill outlines the CoRL 2026 review pipeline, including the OpenReview double-anonymous system, reviewer/AC/SAC hierarchy, scoring thresholds (weak accept), and rebuttal mechanics. It helps authors understand leverage points like the first-round rejection gate and discussion windows to improve acceptance chances.

A comprehensive guide for generating and packaging reproducible evidence for signal processing submissions to ICASSP. It details what reviewers prioritize (scoring scripts, dataset splits, logs) and outlines best practices to ensure that headline metrics are easily regenerated, thereby maximizing review credibility and post-publication impact.

A comprehensive guide for researchers submitting signal processing papers, detailing how to achieve rigorous reproducibility for conferences like ICASSP. It emphasizes that simply providing a model is insufficient; authors must pin down the 'scoring ruler,' data versions, front-end parameters, and computational seeds to ensure every reported metric can be independently verified.

This comprehensive guide details the entire ICSE conference paper review lifecycle, from initial submission to final decision. It analyzes the four core scoring criteria—Novelty, Rigor, Relevance, and Verifiability—and maps out the Accept/Major Revision/Reject decision model. Use this to strategically plan your revisions and understand the academic publishing landscape.

A comprehensive guide for authors planning submissions to MobiSys. It details the two-round review process, the specialized pool of systems-and-services reviewers, and critical scoring dimensions such as on-device evidence, energy/latency rigor, and contribution mechanism. Use this to formulate a robust response strategy for every stage, from initial submission to camera-ready.

This guide helps researchers test whether their economic research question aligns with the specialized scope of top-tier journals, particularly those focusing on dynamic and quantitative mechanisms (like RED). It provides a structured methodology, including fit tests and scoring dimensions (Dynamics, Model, Discipline, Audience), to ensure the core contribution is genuinely dynamic and methodologically rigorous.

This comprehensive guide breaks down the complex SIGGRAPH/SIGGRAPH Asia technical paper review pipeline. It covers the single 6-point scoring scale, the multi-reviewer structure, the rebuttal process, committee decisions, and the dual-track (Journal vs. Conference) outcomes. Use this to understand where authors can exert influence and how to prepare submissions to meet the highest academic standards.

A detailed guide modeling the complex academic review machinery, using SIGIR as a primary example. It covers everything from per-track anonymity regimes and PC-member nomination duties to the critical scoring criteria: evaluating validity, fairness of comparison, and statistical rigor. Essential reading for authors preparing high-stakes research submissions.

Provides a comprehensive, quantitative auditing system for AI agents, skills, and commands. It evaluates these components against industry best practices using a multi-criteria weighted scoring model and assign a production readiness grade (A-F). Ideal for validating complex AI systems before deployment, identifying gaps, and ensuring robust, maintainable code.