Act as a data analysis expert. You are skilled at examining YouTube channels, website databases, and user profiles to gather insights based on specific parameters provided by the user.

Jan 15, 2026

Data

PromptBeginner5 minmarkdownQuality: 20

- Evaluate the structure and data of website databases

identifying trends or anomalies.

Jan 15, 2026

General

PromptBeginner5 minmarkdownQuality: 20

When to clear the snow (generic)

# Generic Driveway Snow Clearing Advisor Prompt

Jan 15, 2026

Data

PromptBeginner5 minmarkdownQuality: 24

1. Accept parameters such as ${platform:YouTube/Database/Profile}

${metrics:engagement/views/likes}

Jan 15, 2026

Find agent skills by outcome

USER INPUT (raw bullets

Based on the recent and forecasted precipitation

Create skills and experience markdown file

- **Expert**: Multiple examples

Additional context: Ask the user for driveway details if helpful (e.g.

# - Gemini 2.5 (by Google): Outstanding for real-time weather integration via Google Search and Maps

# - Copilot (by Microsoft): Integrates Bing weather data for reliable

# - Perplexity AI: Combines conversational AI with instant web searches for up-to-date weather data from sources like NOAA; great for concise

# - GPT-4o (by OpenAI): Highly versatile with strong creative problem-solving

Then

First

# - Claude (by Anthropic): Strong in highly structured

# - DeepSeek R1: Affordable and powerful for logical reasoning and math-based predictions (e.g.

# Goal: To provide data-driven advice on the optimal timing and methods for clearing snow from a driveway

# Audience: Homeowners in snowy regions

- Forecasted snowfall

# Modified Date: December 27

**How**: Key implementation decisions (patterns used

**Risks**: What could break

**Smells**: Tech debt

Detailed Analysis of YouTube Channels, Databases, and Profiles

- Evaluate the structure and data of website databases

When to clear the snow (generic)

1. Accept parameters such as ${platform:YouTube/Database/Profile}

- Expert: Multiple examples

How: Key implementation decisions (patterns used

Risks: What could break

Smells: Tech debt