Skill UI

Arboreto infers gene regulatory networks from bulk or single-cell RNA-seq data using scalable GRNBoost2 and GENIE3 algorithms, letting researchers filter transcription-factor targets, run distributed Dask jobs, and export ranked links for downstream analysis.

Direct Python helpers for KEGG's REST API, covering database metadata, listing, search, retrieval, ID conversion, linkage, and drug interactions to power pathway and gene analysis.

Analyzes oral health records to detect trends, assess caries and periodontal risks, and generate personalized care advice. Supports linked analysis with nutrition, chronic disease, medication, and eye health data for comprehensive oral care insights.

Access live SEO data through DataForSEO MCP tools for SERP analysis, keyword research, backlink profiles, on-page checks, competitor research, and AI visibility tracking. Useful when you need real search results and up-to-date metrics.

A comprehensive, structured framework for conducting sophisticated Open Source Intelligence (OSINT) and cryptocurrency forensic investigations. This guide covers operational security (OpSec), target profiling, advanced transaction tracing across multiple blockchain layers (L1/L2), wallet analysis, and identifying linked digital assets. Use this methodology to guide systematic, multi-dimensional intelligence collection campaigns.

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.

Live AI visibility tracking with SE Ranking API. Measures brand share-of-voice across ChatGPT, Gemini, Perplexity, AI Overviews, and AI Mode, plus SERP, backlinks, and competitor analysis.

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.

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.

A comprehensive guide detailing the rigorous methodologies for conducting and reporting high-level academic research. It covers norms for quantitative, comparative-historical, and computational analyses, emphasizing transparency, reproducibility, robustness checks (e.g., confounders, alternative specifications), and linking claims directly to evidence, suitable for top-tier social science journals.

This guide outlines rigorous standards for conducting heterogeneity analysis in economic research. It stresses that heterogeneity should not merely involve slicing data by region or size, but must be theoretically driven, linking multiple dimensions (e.g., ownership, financing constraints, industry type) to core economic mechanisms. The analysis must demonstrate significant group differences and clearly connect findings to differential policy implications, elevating the discussion from mere observation to actionable policy science.

This guide details the rigorous requirements for achieving research reproducibility in academic publishing. It moves beyond simple data sharing, mandating that authors deposit model-fitting code, analysis scripts, and materials with persistent identifiers (DOI). Key steps include ensuring reported results can regenerate in a fresh session, completing declarations of competing interests, and linking pre-registrations, ensuring compliance with strict journal standards.