Skill UI

Helps product teams structure customer discovery interviews by clarifying goals, segments, constraints, and adaptive methods so each session yields actionable insights instead of confirmation bias or surface-level feedback.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

Guides creators already near product-market fit to grow an organic audience through free, authentic content, consistent scheduling, email ownership, and build-in-public feedback before spending on ads.

A comprehensive multi-agent feedback loop inspired by Generative Adversarial Networks (GANs), designed to build complex, production-ready applications. It separates generation from evaluation, using a 'ruthlessly strict' evaluator (QA) to drive continuous iteration. This process ensures high design quality, robust functionality, and originality, overcoming the limitations of single-agent self-critique. Ideal for full-stack feature development and complex product specification implementation.

Generate a Google Form tailored for event or session feedback and quickly distribute it to participants through Gmail, automating the survey creation and invitation process for productivity boosts.

A comprehensive guide and implementation for configuring the CI/CD pipeline for AppFolio property management APIs. It utilizes a two-tier testing strategy: fast, mocked unit tests for quick feedback, and slower integration tests running against the AppFolio sandbox environment on main branch merges. This ensures robust validation of API interactions and prevents contract drift before production.

A comprehensive workflow for developing and testing financial applications integrated with Fondo. It enables developers to simulate or parse real Fondo exports (CSV/Accounting tools) locally, providing a fast feedback loop for building dashboards, calculating R&D credits, and analyzing burn rates without relying on live API connectivity. Supports mock data for rapid iteration and real export parsing for production validation.

This advanced skill provides highly structured and actionable feedback on any digital or physical design. It applies professional UX frameworks, including Nielsen's Heuristics, Gestalt principles, and Jobs-to-be-Done (JTBD), to evaluate usability, identify critical issues, and provide prioritized, specific recommendations. Ideal for reviewing wireframes, UI screens, user flows, and assessing product completeness.

Provides a structured, outcome-based critique of design concepts, shifting the focus entirely from aesthetics to product viability. This skill is ideal for Product Managers needing to assess whether a design achieves specific user goals, meets core business metrics, and satisfies original requirements. It generates actionable feedback tied to measurable outcomes, ensuring all critique points are evidence-based and strategically relevant.

This skill analyzes raw user research data—including transcripts, survey results, and feedback—and synthesizes it into a structured, actionable report. It identifies key themes, quantifies prevalence, pinpoints critical pain points, prioritizes feature requests, and provides strategic, evidence-backed recommendations for product improvement and development.

A comprehensive skill for systematically monitoring developer conversations across technical platforms like GitHub, Reddit, and Stack Overflow. It helps track brand mentions, competitor positioning, and unsolved technical problems to gather unfiltered product feedback and high-intent leads.

This template transforms complex, multi-source materials (meeting notes, research, product data, financial feedback) into a single, highly structured, actionable one-page memo. It forces the user to distill the core problem, define a clear recommendation, map out tradeoffs, and list actionable next steps, making it ideal for C-level decision-making.