Skill UI

Captures and surfaces Whatsapp activity details so teams can monitor conversations, spot trends, and maintain compliance or support readiness.

Automates PyTorch training workflows by guiding data preparation, model configuration, hyperparameter tuning, and experiment tracking while following industry best practices for production readiness.

A comprehensive checklist designed to ensure TwinMind integrations are deployed securely, stably, and compliantly in a production environment. It covers critical best practices across multiple domains, including authentication, data encryption (PII, GDPR), robust infrastructure setup (auto-scaling, load balancing), advanced monitoring (metrics, tracing, alerting), and full CI/CD deployment workflows. Use this when preparing for go-live or conducting production audits.

This expert skill validates the deployment readiness of Vertex AI Agent Engines. It executes a weighted audit across five critical dimensions: security, monitoring, performance, compliance, and best practices. The output provides a comprehensive 0-100% composite score, a detailed pass/fail report for each check, and a prioritized, actionable remediation plan, ensuring high-quality, production-grade deployments.

Provides automated guidance for designing, validating, and deploying Vertex AI pipelines within Google Cloud, covering compute, storage, BigQuery, and GCP-specific services for production readiness.

This skill thoroughly inspects and validates Vertex AI Agent Engine deployments. It assesses critical components such as the Code Execution Sandbox, Memory Bank, A2A protocol compliance, security posture, and performance metrics. The tool generates weighted production-readiness scores (0-100%) and provides detailed, actionable recommendations to ensure the deployment is robust, secure, and ready for production use.

Interactive assessment that gauges whether your product work is AI-first or AI-shaped, measures readiness across five essential PM competencies for 2026, highlights gaps, and recommends which AI capability to build next.

This comprehensive guide facilitates the development of a production-ready Minimum Viable Product (MVP) for a SaaS business. It covers the entire lifecycle, including idea validation, modern tech stack selection (Next.js, Supabase, Stripe), architectural design for multi-tenancy, database schema planning, authentication setup, payment integration, and a detailed pre-launch checklist for technical and marketing readiness.

Coaches directors and senior product leaders through the leap to VP or CPO by diagnosing where they are in the journey, surfacing the unique constraints at that level, and offering adaptive questions and practical coaching tailored to preparing, interviewing, landing, and recalibrating.

Performs a comprehensive website SEO audit, crawling up to 500 pages, checking technical issues, content quality, schema, performance, and AI search readiness. Useful for site health checks, SEO reviews, and prioritized improvement plans.

Analyze a website for AI search visibility across Google AI Overviews, ChatGPT search, and Perplexity. Checks citability, structure, brand signals, crawler access, and llms.txt readiness to improve generative engine optimization.

Performs a full GEO audit of any website by discovering business type, crawling prioritized pages, and delegating parallel subagents to evaluate AI visibility, platform readiness, technical infrastructure, EEAT content, and schema markup, then outputs a composite GEO score with prioritized actions.