Skill UI

A comprehensive skill for creating, editing, and automating complex spreadsheet workflows using LibreOffice Calc. This includes generating new ODS files, performing format conversions (XLSX, CSV, PDF, etc.), executing advanced formulas, and automating data processing through Python scripting (UNO, ezodf) or command-line interfaces. Ideal for data analysis, reporting, and batch processing tasks.

A comprehensive guide for designing production-grade lead enrichment pipelines in Clay. Covers three integration patterns (Webhook, API), detailed table schema design, advanced data waterfall logic, implementing complex ICP scoring formulas, and setting up robust CRM synchronization flows for go-to-market data operations.

Applies empirically grounded cognitive science frameworks to help CS and AI researchers generate genuinely novel directions through bisociation, analogical reasoning, constraint shifts, and problem reformulation workflows.

Automates Coda document and data workflows through Rube MCP/Composio, covering searches, tables, formulas, exports, permissions, sharing, and publishing so bots can manage docs without manual API fiddling.

A systematic, multi-phase guide for tackling hard bugs and performance regressions. It mandates building a robust feedback loop (e.g., failing tests, harnesses), formulating falsifiable hypotheses, targeted instrumentation, and rigorous regression testing. This methodology ensures that debugging efforts are structured, efficient, and highly reproducible, making it ideal for complex software defects.

This skill details advanced techniques for exploiting formula injection vulnerabilities within CSV, Excel, LibreOffice, and Google Sheets environments. It covers DDE, obfuscation methods, and high-risk functions like IMPORT* that can be triggered when user-controlled data is exported or imported into spreadsheet software. Use this for penetration testing of data pipelines and export features.

This skill provides comprehensive guides and references for writing, debugging, and systematically optimizing DAX formulas within semantic models. It covers advanced topics including systematic performance optimization workflows, engine internals (like xmSQL), and best practices for both local (Power BI Desktop) and remote (Fabric/XMLA) model environments, ensuring efficient data calculation and query performance.

A comprehensive reference guide providing quantitative benchmarks and formulas for system architects. It covers user-to-RPS conversion, storage estimation, bandwidth calculation, known scale limits of major technologies (databases, queues, caches), and capacity planning for various user loads (1K DAU to 10M DAU). Essential for designing scalable, high-availability applications.

This guide provides a rigorous, step-by-step framework for developing robust academic theories, particularly for prestigious journals like the Academy of Management Review (AMR). It shifts the focus from simple assertions to a structured argument by requiring explicit definition of constructs (including domain and scope), stating underlying assumptions, specifying relationship forms (e.g., mediating, causal), articulating the mechanism (the 'why'), and formulating falsifiable, numbered propositions. Mastering this process ensures the theory is comprehensive and academically sound.

This skill guides researchers in transforming a simple empirical finding into a robust, testable theoretical contribution suitable for high-level communication journals. It structures the argument by defining precise constructs, articulating the communication mechanism (mediator), identifying boundary conditions (moderators), and formulating explicit, numbered hypotheses. It shifts the focus from merely reporting an effect to detailing the underlying theoretical process and causal ordering.

This comprehensive guide outlines the necessary theoretical rigor for algorithms and models submitted to top-tier computational journals. It instructs authors on how to formally state mathematical formulations, rigorously prove model validity, establish convergence, and quantify complexity (e.g., approximation ratios, finite termination). It provides specialized paths for exact methods, metaheuristics, and ML-enhanced OR, ensuring that the theoretical advancements fully support and rationalize the experimental findings.

This guide provides a rigorous framework for developing robust, theory-driven hypotheses in accounting research, especially for high-impact academic journals. It teaches researchers how to transition from observing mere correlations to formulating hypotheses grounded in established economic theories, such as agency theory, information economics, and positive accounting theory. The process emphasizes identifying the core economic friction, naming the acting agents and their incentives, and deriving directional, falsifiable, and a priori predictions.