Skill UI

This guide helps scholars assess if their social, economic, or cultural history manuscript aligns with the rigorous, problem-driven standards of Past & Present. It instructs authors on framing their research around a core "big question"—a genuine historical problem—ensuring comparative significance, adhering to historiographical expectations, and meeting specific academic standards like double-blind review and Chicago style.

Scans your local machine's Git history to locate abandoned or unfinished side projects. It performs a deep 'autopsy' on these repositories, determining their causes of death (e.g., deployment fear, killed by newer ideas) and identifying personal developmental patterns. The tool then surfaces the most promising candidate for resurrection, helping you finally ship it.

This guide outlines the strategic process for authors responding to major or minor revisions (R&R) for academic journals, particularly in public administration. It teaches how to structure a diplomatic, point-by-point rebuttal letter that satisfies both expert reviewers and handling editors. Key strategies include reconciling conflicting demands, explicitly addressing every comment, and protecting the paper's core scholarly contribution and practical evidence.

This tool assists researchers in assembling and rigorously validating a complete replication package for academic submission. It checks the master script, pinned environment, data plan, and methodology against specific journal policies, ensuring that every reported number is reproducible and deterministic, preventing 'my machine' errors.

A comprehensive guide for authors submitting to SIGMETRICS, detailing how to structure the Related Work section. It emphasizes shifting from a simple citation catalog to a 'delta-first' contrast, highlighting the specific technical novelty (e.g., tighter bounds, weaker assumptions) relative to existing literature across multiple performance evaluation lanes (systems, measurement, learning, etc.).

This guide provides rigorous best practices and structural templates for authors submitting to sociological journals. It emphasizes moving beyond mere background description to focus on the core sociological problem, mechanism, key findings, and theoretical contribution, while adhering to strict length constraints for both English and Chinese abstracts.

This skill provides a comprehensive guide for evaluating whether a research manuscript aligns with the scope, structure, and requirements of the journal *Soft Science*. It covers journal positioning, topic preferences, recommended writing structure, common rejection pitfalls, and strategic revision advice for academic papers focused on policy, regional development, and management decision-making.

Cirq is a powerful, open-source Python framework developed by Google Quantum AI. It allows users to design, simulate, and execute complex quantum circuits. It supports advanced features including parameterized circuits, noise modeling, circuit transformation, and seamless integration with multiple quantum hardware backends (e.g., IonQ, Google Quantum, Pasqal).

This skill generates high-quality images, textures, icons, and visual assets from text prompts using advanced AI models. It supports multiple providers, including OpenAI (DALL-E) and Google Gemini, offering flexibility in quality and speed. Ideal for rapid prototyping, game asset creation, artwork, and visual mockups across various projects. Requires configuration with an API key.

gget is a versatile CLI and Python package designed for rapid, reproducible bioinformatics searches across major genomic reference databases (e.g., Ensembl, UniProt). It allows users to quickly query gene metadata, perform initial BLAST/BLAT style alignments, and explore associated pathways, cancer, or disease modules. It is ideal for initial data exploration and generating reproducible evidence logs before building complex, full-scale local pipelines.

NetworkX is a powerful Python package designed for creating, manipulating, and analyzing complex networks and graphs. It supports various graph types (Directed, Undirected, MultiGraphs) and provides extensive functionality for graph algorithms, including shortest path calculation, centrality measures (like PageRank), community detection, and connectivity checks. Users can generate synthetic networks, read/write data from multiple formats (GraphML, CSV, Pandas), and visualize results using Matplotlib. Ideal for social network analysis, biological research, and system modeling.

Polars is a lightning-fast DataFrame library designed for efficient, memory-efficient data processing in Python and Rust. Built upon Apache Arrow, it supports lazy evaluation and parallel execution, making it ideal for ETL pipelines, large-scale data transformations, and scenarios where standard Pandas performance is insufficient. It excels at handling datasets up to 100GB that fit within available RAM.