Skill UI

A comprehensive guide for academic authors on writing balanced, unbiased, and rigorous literature reviews. It teaches how to manage the fundamental tension between comprehensive coverage (ensuring nothing important is missed) and selective emphasis (foregrounding the most critical arguments). The framework ensures fairness across diverse theoretical schools, methodologies (quantitative, qualitative, etc.), and competing findings, while explicitly guarding against self-citation bias.

This guide helps authors sharply frame their econometric research contributions, specifically tailored for high-impact academic journals like The Econometrics Journal (EctJ). It enforces a strict four-part structure: identifying failure modes of incumbent methods, stating the smallest sharp advance, detailing the applied payoff, and establishing scope guardrails. This ensures the core novelty and practical value are immediately obvious to reviewers.

A comprehensive guide for authors to select, defend, and strengthen the internal validity of clinical study designs (RCT, Cohort, Diagnostic, etc.). It provides detailed safeguards—covering topics like intention-to-treat analysis, confounding control, blinding, and power calculations—to ensure manuscripts meet the rigorous reporting standards of top-tier medical journals like JAMA.

This module provides a lazy adapter registry to seamlessly integrate OpenMed's clinical PII detection with major NLP frameworks like Microsoft Presidio, spaCy, and LangChain. It allows users to use OpenMed for enhanced PII recall, merge spans, or implement on-device PHI redaction guardrails without rewriting entire pipelines.

This skill implements a comprehensive logging guard to prevent Protected Health Information (PHI) leakage into logs, traces, and error reports. It acts as a pre-emission filter, redacting structured identifiers (SSN, email, phone) via regex and handling free-text PHI using advanced models. Essential for maintaining strict data privacy and compliance when shipping logs to centralized stores or error trackers.

A sophisticated, multi-agent system designed to perform deep, comprehensive code reviews on pull requests. It covers core elements like code quality, functionality, security vulnerabilities, and testing coverage. Advanced features include detecting scope drift, enforcing SOLID principles, identifying DRY violations, and providing anti-hallucination safeguards for maintain high software integrity.