Skill UI

A comprehensive guide for planning rigorous scientific studies in Earth and Planetary Sciences, covering sampling, analytical campaigns, experimental runs, and modeling. It ensures that research designs are robust, addressing critical elements like sample context, traceability to reference materials, replication levels, and falsifiability before data collection begins. Essential for high-impact scientific publishing.

This guide assists in structuring the design of Environmental Science & Technology (ES&T) studies, including lab, mesocosm, field sampling, or modeling experiments. It ensures methodological rigor by planning for environmental relevance, necessary controls (e.g., abiotic loss, sorption), proper replication, mass/energy balance, and a comprehensive QA/QC plan from the outset, helping the study withstand expert peer review.

This guide outlines the rigorous methodology for ensuring that computational research results, especially those involving hardware architecture and simulation, are fully reproducible. It emphasizes pinning the entire result chain—from simulator commits and configuration files to workloads, sampling recipes, and statistics scripts—and mandates creating a manifest for every figure. Key practices include recording machine state for silicon runs and containerizing the environment to prevent data drift.

This guide provides rigorous standards for designing, validating, and reporting security research, particularly for high-stakes academic conferences like IEEE S&P. It covers critical areas including adaptive adversary modeling, measurement validity (sampling, ethics), statistical reporting, establishing strong baselines/ablations, and adhering to ethical constraints (IRB, authorization) to ensure evidence is robust and reproducible.

A comprehensive guide for conducting rigorous empirical analysis on field and survey data in low- and middle-income settings. It covers advanced methods for handling clustered sampling, measurement error, differential attrition, and treatment-effect heterogeneity, ensuring results meet the high standards of reproducibility and robustness required by leading developmental economics journals.

A comprehensive methodology guide for designing rigorous multi-country or cross-cultural studies, essential for international marketing research. It covers critical steps such as country selection criteria, ensuring construct, translation, and sampling equivalence, and planning for measurement invariance (MGCFA). It guides researchers through advanced designs including cross-cultural experiments, multi-level estimation, and handling secondary export/entry-mode data.

This guide details the rigorous peer-review process for the Journal of Operations Management (JOM). It covers the department-routed structure, the specific rules of asymmetric double-anonymous review, and the critical method checks (sampling, measurement, identification) required for empirical submissions. It helps authors understand how to interpret complex decision letters and improve their manuscript quality.

A comprehensive guide for auditing survey methodology, focusing on the Total Survey Error (TSE) framework required by top-tier academic journals like Public Opinion Quarterly (POQ). It provides detailed steps to rigorously defend every methodological element—including coverage, sampling, nonresponse, weighting, and measurement—to meet AAPOR standards. This is a critical tool for strengthening research rigor before submission.

Guideline for front-end JavaScript reverse engineering using js-reverse MCP tools and jshookmcp. Covers locating signature and encrypted parameters, tracing request initiators, runtime sampling via hooks, local Node environment reconstruction, and evidence-first output for reproducing signing logic.

This tool separates an already generated music production into four isolated stems: vocals, drums, bass, and other. It is ideal for users needing to remix tracks, create karaoke versions, or perform music sampling. Requires an existing production ID, and the resulting stems are accessible via the primary dashboard.

Python low-level exporter for sending OpenTelemetry traces, metrics, and logs to Azure Application Insights. Supports custom pipelines, sampling, Azure AD auth, and offline storage.

One-line setup of Azure Monitor Application Insights for Python apps using OpenTelemetry auto-instrumentation. Covers Flask, Django, FastAPI, custom traces, metrics, logs, sampling, and AAD auth.