Skill UI

A specialized assistant for sourcing and ordering W-2 compliant temporary staff for large-scale events such as conventions, trade shows, festivals, and concerts across 300+ US and Canadian markets. It validates city coverage, retrieves role pricing, checks availability, and surfaces state compliance requirements using live data tools before guiding the user to submit the final staffing request.

This meta-skill provides an auditable workflow for professional compliance self-assessments (e.g., GDPR, SOC2). It executes deep research while retaining citation evidence, then compiles the findings into a comprehensive package: a signable DOCX report, a read-only PDF archive for permanence, and a persistent memory note to guarantee the evidence chain is recallable. Ideal for structured policy auditing.

This meta-skill implements a combinator pattern for deep security analysis. It runs three independent gates—policy governance, secret scanning, and audit logging—over a candidate operation. It enforces a strict arbitration rule (Policy DENY > Scanner WARN > ALLOW) to provide a robust, multi-layered verdict, making it ideal for reviewing critical code changes or environment modifications for safety compliance.

This automated workflow performs a comprehensive review against the AWS Well-Architected Framework (WAF). It scans IaC definitions (Terraform, CloudFormation, CDK) and deployed resources to identify compliance gaps, security risks, and optimization opportunities across six core pillars. Findings are structured and automatically generated as actionable GitHub issues with remediation code examples.

An expert skill for generating, auditing, and improving Best Practice Analyzer (BPA) rules for Power BI semantic models. It guides users through an interactive, multi-phase Q&A process (Double Diamond) to gather comprehensive requirements, analyze model structures, and deliver tailored, actionable rule sets for governance and compliance.

This skill provides tools to audit, enforce, and standardize Power BI report themes. It addresses 'formatting debt' by centralizing bespoke visual overrides into the theme JSON, ensuring global consistency. Use it when reports suffer from formatting inconsistency, or when manual visual formatting has cluttered the visual JSON, allowing developers to maintain a clean, scalable report structure.

This skill maps engineering changes (code diffs, architecture designs, IaC) to specific financial compliance controls, such as PCI-DSS v4.0 and MAS TRM. It generates an auditable report detailing compliance gaps, required evidence, and concrete remediation steps, helping teams catch violations before formal audits.

A structured, multi-phase skill that systematically audits and provides actionable fixes for all four Lighthouse pillars: Performance, Accessibility, Best Practices, and SEO. It analyzes Core Web Vitals, render-blocking resources, security headers, and ARIA compliance to significantly boost site speed and quality.

A detailed, comprehensive reference guide covering best practices for securing modern applications. This checklist spans network architecture, API design, data encryption, authentication protocols, and regulatory compliance (GDPR, HIPAA, PCI-DSS), ensuring robust security across the entire technology stack.

This skill provides a highly rigorous framework for analyzing complex public issues, platform governance, and institutional compliance. It is designed to structure evidence boundaries, assess procedural justice, and track public commitments by synthesizing source ledgers and multiple data points. It is intended as a specialized sub-routine triggered by the main CrossFrame suite, not for standalone use. Key focus areas include source verification, identifying weak signals, and mitigating AI compliance performance risks.

Conducts a comprehensive, structured ethical review for any AI or ML model, feature, or product. It assesses risks related to fairness, bias, transparency, privacy, and societal impact, providing a risk tier score, necessary mitigations, and governance documentation suitable for pre-deployment compliance.

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.