Skill UI

Comprehensive Python toolkit for building, analyzing, and visualizing complex networks; supports algorithms, I/O, generation, and community detection across social, biological, transportation, and citation data.

This powerful tool facilitates comprehensive market research by extracting diverse data points from major consumer and business platforms, including Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor. It is designed to provide structured data for market sizing, analyzing regional demand, tracking pricing trends, and validating consumer behavior, enabling users to identify actionable business opportunities and potential risks.

Guides product and growth teams through evaluating whether to scale, test, or kill acquisition channels using unit economics (CAC, LTV, payback), customer quality (retention, NRR), and scalability indicators for data-driven go-to-market budgeting.

Interactive guidance that evaluates SaaS growth, retention, unit economics, and capital efficiency together so leaders can surface red flags, prioritize fixes, and prepare board or investor reviews.

Guides product managers through adaptive customer journey mapping workshops, clarifying persona, goals, phases, emotions, and opportunities to uncover pain points and align teams before roadmap decisions.

Guides product managers from stakeholder requests to structured Opportunity Solution Trees by extracting outcomes, enumerating opportunities, mapping solutions, and evaluating experiments to select the best proof of concept before building.

Guide teams through a structured PESTEL assessment of external political, economic, social, technological, environmental, and legal forces to surface risks and opportunities for product strategy, market entry, and long-term planning.

Analyzes SaaS unit economics and capital efficiency to guide PMs and leaders on CAC, LTV, payback, burn, runway, and Rule of 40 trade-offs before scaling or fundraising.

This comprehensive guide outlines a rigorous, human-in-the-loop engineering workflow for leveraging advanced AI agents to complete complex implementation tasks. It mandates defining clear completion criteria, decomposing work into manageable units, and strategically routing models (Haiku, Sonnet, Opus) based on task complexity. The workflow emphasizes continuous evaluation, regression testing, security review of invariants and edge cases, and strict cost discipline to ensure robust and reliable software development using AI assistance.

Guides startup CFOs and finance leaders through strategic modeling, fundraising roadmaps, cash management, unit economics analysis, and investor-ready board packages so decisions stay grounded while extending runway and protecting growth.

Guides building custom Odoo modules by scaffolding manifests, models, views, and security rules, reviewing existing code, and applying ORM best practices across Community and Enterprise editions.

This advanced pipeline orchestrates complex feature development based on Request for Comments (RFCs). It breaks down monolithic changes into small, independently verifiable work units, managing dependencies through a Directed Acyclic Graph (DAG). It includes multiple quality gates, dedicated unit testing, and a safe merge queue to ensure robust integration and controlled deployment.