How do I install the Product Pro skill?

Run npx skillmds@latest add yuniorglez/product-pro in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Product Pro safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Product Pro?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Product Pro free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Product Pro?

yuniorglez (@yuniorglez) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Product Pro by yuniorglez — Agent Skill

Name: Product Pro
Author: yuniorglez

File contents

🚀 Skill: Product Pro (v1.1.0)

Executive Summary

The product-pro is the orchestrator of the product's vision, strategy, and "Magic Moments." In 2026, Product Management has evolved from managing deterministic backlogs to curating Probabilistic AI Loops. This skill focuses on building products that "Think," leveraging Agentic Workflows for rapid validation, and maintaining Strategic Integrity in a world of high-velocity AI development.

🏛️ AI Product Philosophies

Confidence over Certainty: Design for probabilistic outcomes. What happens at 70% confidence?
Magic Moments First: Focus on the core reasoning loop that provides 80% of the value.
Context is the Moat: The more your AI knows about the user's domain, the harder you are to replace.
Agentic Velocity: Use AI agents to build and test prototypes in days.
Ethical Guardianship: Ensure that AI decisions are transparent, biased-free, and secure.

🚫 The "Do Not" List (Anti-Patterns)

Anti-Pattern	Why it fails in 2026	Modern Alternative
Deterministic Roadmaps	AI features fail or pivot rapidly.	Use Experiment Loops.
Silent AI Failures	Destroys user trust instantly.	Use Graceful Uncertainty UI.
"AI for AI's Sake"	High cost, low business value.	Problem-First Integration.
Thin Context	Leads to hallucinations.	Context Engineering.
Ignoring Data Privacy	Legal and brand catastrophe.	Privacy-by-Design Architecture.

🧪 Scientific Hypothesis Generation

We use a rigorous method to test AI improvements:

Observation: "Users are confused by Feature X."
Hypothesis: "If we add a Reasoning Agent to Feature X, then completion rate will rise 20%."
Experiment: Build a minimal agentic prototype.
Validation: Measure helpfulness and accuracy logs.

📖 Reference Library

Detailed deep-dives into AI Product Excellence:

AI Product Strategy: Navigating the probabilistic era.
Rapid Prototyping: Building with agentic velocity.
Context Engineering: Curating truth for AI agents.
Hypothesis Criteria: Framework for rigorous testing.

Updated: January 22, 2026 - 20:30

---name: product-prodescription: Senior AI Product Manager. Expert in Probabilistic Strategy, Rapid Agentic Prototyping, and Hypothesis Generation for 2026.---# 🚀 Skill: Product Pro (v1.1.0)## Executive SummaryThe `product-pro` is the orchestrator of the product's vision, strategy, and "Magic Moments." In 2026, Product Management has evolved from managing deterministic backlogs to curating **Probabilistic AI Loops**. This skill focuses on building products that "Think," leveraging **Agentic Workflows** for rapid validation, and maintaining **Strategic Integrity** in a world of high-velocity AI development.---## 📋 Table of Contents1. [AI Product Philosophies](#ai-product-philosophies)2. [The "Do Not" List (Anti-Patterns)](#the-do-not-list-anti-patterns)3. [Scientific Hypothesis Generation](#scientific-hypothesis-generation)4. [AI Product Strategy](#ai-product-strategy)5. [Rapid Agentic Prototyping](#rapid-agentic-prototyping)6. [Context Engineering for PMs](#context-engineering-for-pms)7. [Reference Library](#reference-library)---## 🏛️ AI Product Philosophies1. **Confidence over Certainty**: Design for probabilistic outcomes. What happens at 70% confidence?2. **Magic Moments First**: Focus on the core reasoning loop that provides 80% of the value.3. **Context is the Moat**: The more your AI knows about the user's domain, the harder you are to replace.4. **Agentic Velocity**: Use AI agents to build and test prototypes in days.5. **Ethical Guardianship**: Ensure that AI decisions are transparent, biased-free, and secure.---## 🚫 The "Do Not" List (Anti-Patterns)| Anti-Pattern | Why it fails in 2026 | Modern Alternative || :--- | :--- | :--- || **Deterministic Roadmaps** | AI features fail or pivot rapidly. | Use **Experiment Loops**. || **Silent AI Failures** | Destroys user trust instantly. | Use **Graceful Uncertainty UI**. || **"AI for AI's Sake"** | High cost, low business value. | **Problem-First Integration**. || **Thin Context** | Leads to hallucinations. | **Context Engineering**. || **Ignoring Data Privacy**| Legal and brand catastrophe. | **Privacy-by-Design Architecture**. |---## 🧪 Scientific Hypothesis GenerationWe use a rigorous method to test AI improvements:1. **Observation**: "Users are confused by Feature X."2. **Hypothesis**: "If we add a Reasoning Agent to Feature X, then completion rate will rise 20%."3. **Experiment**: Build a minimal agentic prototype.4. **Validation**: Measure helpfulness and accuracy logs.---## 📖 Reference LibraryDetailed deep-dives into AI Product Excellence:- [**AI Product Strategy**](./references/ai-product-strategy.md): Navigating the probabilistic era.- [**Rapid Prototyping**](./references/rapid-prototyping-agentic.md): Building with agentic velocity.- [**Context Engineering**](./references/context-engineering-pm.md): Curating truth for AI agents.- [**Hypothesis Criteria**](./references/hypothesis_quality_criteria.md): Framework for rigorous testing.---*Updated: January 22, 2026 - 20:30*

Frequently asked questions

Product Pro