Skill UI

This comprehensive canvas guides teams through developing robust AI-powered features. It ensures product decisions are rigorous by covering problem definition, model selection (LLM, RAG, etc.), data governance, evaluation metrics, user experience design (including fallbacks), and responsible AI compliance. Ideal for assessing AI readiness and preventing common product failures.

This skill provides comprehensive monitoring advisory services for data assets and AI agents. It helps users assess data coverage gaps, analyze use-case criticality, and automatically create data quality monitors (table, metric, validation). Furthermore, it enables monitoring of AI agent performance, latency, and observability, ensuring robust data governance across the entire ML lifecycle.

This skill analyzes your data warehouse to pinpoint stale, unused, or redundant tables that contribute to unnecessary storage costs. It classifies waste patterns (e.g., Zombie, Temporary) and computes safety tiers, helping users understand which assets can safely be dropped or archived to optimize spending and improve data governance.

This tool facilitates bi-directional synchronization of marketing data (contacts, deals, campaigns) between connected CRM platforms, including Salesforce, HubSpot, Zoho, and Pipedrive. It ensures a single source of truth for sales and marketing by handling automatic field mapping, data deduplication, compliance validation (e.g., GDPR), and advanced conflict resolution. Designed for complex, enterprise-grade data governance, this method replaces manual CSV imports for reliable, governed data transfers.

A comprehensive guide designed to help researchers evaluate the suitability of their manuscript for 'China Rural Survey.' It covers the journal's academic scope, key thematic interests (e.g., land tenure, rural governance), required structural elements, and critical submission protocols (such as double-blind review, data/code public disclosure, and abstract formatting). Use this tool to refine your argument and ensure compliance before formal submission.

This skill provides a comprehensive framework for authors aiming to submit to the prestigious journal 'E-Government.' It guides users on assessing manuscript fit, aligning research with the journal's focus on digital governance, data element, public value, and administrative reform. It covers scope definition, required methodology, structural adjustments, and mandatory formatting checks.

This guide outlines the best practices and norms for executing and reporting empirical analyses in governance and comparative political science. It covers essential methods including cross-national inference, clustering uncertainty, robustness checks, multi-method triangulation, and ensuring reproducibility, guiding researchers to conduct rigorous, publication-ready studies.

This guide provides a comprehensive preflight checklist for authors submitting academic manuscripts to major journals (e.g., Wiley/Governance). It ensures compliance with critical submission requirements, including double-blind anonymization, strict word count limits, abstract length, Data Availability Statements, and adherence to specific scholarly scopes. Use this before hitting submit to minimize desk rejection risks and submission errors.

This skill guides users on whether their international economics manuscript fits the scope, theoretical depth, and methodological requirements of the International Economic Review. It analyzes the journal's focus (global governance, open policies), required evidence (FDI, GVC, cross-country data), and common submission pitfalls, helping authors improve manuscript structure and increase acceptance chances.

This guide helps authors refine academic prose for institutional and organizational economics journals. It teaches how to structure the narrative to open with an institutional puzzle, clearly name the underlying mechanism, and frame the contribution as a delta on a specific frontier, ensuring the focus remains on governance and organizational forms rather than just data or models.

Designed for regulated environments (GxP/GCP), this skill generates and verifies audit trails compliant with 21 CFR Part 11 standards. It ensures every data processing step leaves an attributable, time-stamped, and tamper-evident record, providing electronic signatures and robust data integrity checks (ALCOA+). It is essential for clinical trials and regulated data governance.

This skill automates the creation of comprehensive Model Cards for OpenMed clinical NER or de-identification models. It gathers data from various OpenMed evaluation reports (e.g., `GateReport`, `fairness_report`, `error_report`) to structure critical governance information, including intended use, quantitative performance metrics, subgroup analysis, limitations, and required medical-device disclaimers. It ensures documentation is reproducible and compliant for clinical AI deployment.