Skill UI

An expert skill for creating highly optimized, minimal, and fast-starting Windows installers for Python applications. Utilizing advanced techniques like Nuitka's extreme compilation, DLL footprint analysis, and Inno Setup packaging. This process ensures a clean, professional, and resource-efficient deployment, suitable for commercial products, rather than basic script conversion.

A comprehensive set of programmatic interfaces for RuView's Wi-Fi sensing capabilities, including the CLI binary, REST API, and WebAssembly builds. This toolkit allows developers to integrate sophisticated disaster survivor detection and signal analysis into various environments, such as scripting, web browsers, and edge devices (ESP32-WASM3). Ideal for systems requiring cross-platform, scalable sensing data streams.

Perform comprehensive, granular SEO audits on a single URL. This tool examines title tags, meta descriptions, content depth, E-E-A-T signals, technical health (Core Web Vitals, canonical tags), and AI search readiness. Ideal for landing page optimization, content auditing, and ensuring compliance with the latest Google guidelines.

This skill performs a deep technical SEO analysis, diagnosing fundamental website issues related to search engine visibility and performance. It covers optimizing Core Web Vitals, improving crawlability via robots.txt and sitemaps, fixing rendering problems (JavaScript SEO), managing complex redirects, and ensuring optimal site architecture. Use it for comprehensive site audits, migrations, and performance tuning.

A comprehensive guide outlining rigorous data analysis and reporting standards for geographic manuscripts. It covers spatial statistics, remote sensing accuracy, and qualitative interpretation, emphasizing spatial honesty, quantifying uncertainty, and ensuring results are robust across different scales and units.

This tool serves as an orchestrator for manuscripts submitted to the Annals of the AAG. It guides authors through the complex submission process by helping define the appropriate academic area (e.g., Human Geography, Physical Geography), the article format (Article, Commentary), and the sequential developmental stages—from topic selection and theory building to data analysis and final submission. It ensures the work is framed legitimately as *geography*.

A comprehensive guide for building and strengthening the conceptual or theoretical framework for academic manuscripts, particularly for submission to top-tier journals like AERJ. It teaches researchers how to ensure that theory drives the entire study—from question generation and design choices to data analysis and interpretation—transforming findings from mere reports into genuine theoretical contributions.

This guide details the rigorous data analysis and reporting standards required for top-tier academic journals, such as AJPS. It focuses intensely on reproducibility, ensuring that all results—from primary findings to exploratory models—are generated by a single, seeded master script. Key requirements include reporting uncertainty intervals, proving robustness, adhering to pre-registration discipline, and accommodating mandatory third-party code verification. Use this when conducting complex empirical research in social sciences or political science, needing to withstand intensive methodolo...

A comprehensive guide for strengthening the methodological rigor of academic manuscripts, particularly for high-stakes journals. It covers advanced techniques for causal identification (e.g., Difference-in-Differences, Instrumental Variables, Regression Discontinuity), pre-analysis planning, linking theory to empirical tests, and defending claims against skeptical reviewers. This skill focuses on methodological architecture, not code.

This guide provides detailed standards for planning, auditing, and executing data analysis for sociological manuscripts, specifically tailored to the standards of the American Journal of Sociology (AJS). It stresses that analysis must credibly support a theoretical claim, rather than simply showcasing technical proficiency. Key areas covered include quantitative robustness checks, comparative-historical logic, ethnographic procedure, and the crucial principle of triangulation across diverse data sources.

A comprehensive guide for structuring and defending the methodological design of social science manuscripts, particularly for high-impact journals like AJS. It covers diverse traditions—including quantitative, comparative-historical, ethnographic, and network analysis—ensuring the design rigorously supports the theoretical claim, rather than just presenting data. Use this when justifying case selection, identifying assumptions, or linking field observations to major theoretical arguments.

This skill serves as the central workflow router for manuscripts submitted to the American Journal of Sociology (AJS). It guides authors through the entire academic lifecycle, from initial topic selection and theoretical framing to research design, data analysis, and final submission/rebuttal. It helps authors determine the appropriate next step based on the manuscript type (research article, comment, reply) and current stage, ensuring the work meets AJS's high standard for theoretical ambition and sociological dialogue.