AI Service Researcher Skill

This skill guides an AI agent through a rigorous, highly structured product and UX research process for AI services, SaaS tools, and MCP (Model Context Protocol) servers. It produces clean, standardized research documentation optimized for design and product planning teams.

When to Use This Skill

Activate this skill when the user asks to:

• Benchmark or research AI services, SaaS products, or MCP tools.
• Analyze the User Experience (UX), Micro-interactions, or Automation Workflows of an AI service.
• Generate a product research report or comparison matrix for product design/planning.

Core Principles

1. Structured UX Focus: Always evaluate beyond surface features—analyze value proposition, onboarding UX, key micro-interactions, integration ecosystem (MCP/API), and pricing.
2. Clear Architecture: Separate functional capabilities from user experience design patterns.
3. Actionable Insights: Provide concrete design and product recommendations, not just high-level descriptions.

Research Output Template

When performing AI service research, structure the final Markdown output according to the following framework:

# [Service Name] Product & UX Research Report

**Date:** YYYY-MM-DD  
**Category:** [e.g., LLM Agent / Design System / Workflow Automation / MCP Server]  
**Target Audience:** [e.g., UI/UX Designers, Product Managers, Developers]  

---

## 1. Service Overview & Value Proposition
- **Core Summary:** Concise 2-line summary of what the service does.
- **Key Problem Solved:** What specific user pain point does it address?
- **Primary Value Proposition:** Why users choose this over existing alternatives.

---

## 2. Key Features & Integration Capabilities
| Feature / Tool | Functionality | Technical / API / MCP Context |
| :--- | :--- | :--- |
| **Feature 1** | Description of main capability | Integration level (e.g., MCP Server, REST API, Webhook) |
| **Feature 2** | Description of main capability | Integration level |

---

## 3. UX & Micro-Interaction Analysis
- **Onboarding & Time-to-Value:** How fast can a user get the first meaningful output?
- **Key Micro-interactions & Feedback:**
  - Status/Feedback mechanisms (e.g., toast notifications, streaming states, skeleton loaders).
  - Emotional/Delight elements (motion effects, micro-animations).
- **Usability & Pain Points:** Friction points observed in the user flow.

---

## 4. Competitive Positioning & Matrix

| Criteria | [Service Name] | Competitor A | Competitor B |
| :--- | :--- | :--- | :--- |
| **Core Strengths** | | | |
| **Target UX Focus** | | | |
| **Ecosystem / MCP** | | | |
| **Pricing Tier** | | | |

---

## 5. Summary & Product/UX Takeaways
- **Design Recommendations:** Key takeaways for UI/UX teams building similar experiences.
- **Workflow Automation Potential:** How this service fits into n8n, MCP, or agentic pipelines.

Step-by-Step Research Workflow

1. Information Gathering: Collect details on core functionality, UX patterns, and technical integrations.
2. UX Analysis: Evaluate accessibility, micro-interactions, feedback mechanisms, and user onboarding friction.
3. Synthesis: Populate the Research Output Template with precise, objective analysis.
4. Actionable Takeaways: Provide specific recommendations tailored for product planners, designers, and developers.