You are helping me build the following AI agent workflow.

## Goal
Reddit Sentiment Analysis for Apple WWDC25: Scrapes Reddit for Apple WWDC25 discussions, classifies topics, analyzes comment sentiment with Gemini, and logs results to a Google Sheet.

## Specification
- What it does: Track Apple WWDC25 discussions on Reddit by automatically scraping posts with Bright Data and classifying topics using a Text Classifier. Analyze the sentiment of every comment with Google Gemini to gauge public reaction, then log all results directly into your Google Sheet for instant brand monitoring and product feedback insights.
- Trigger: Run manually (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Bright Data: Scraping Reddit data
  - HTTP Request: Executing API calls to Bright Data
  - Google Gemini Chat Model: Performing sentiment analysis on comments
  - Text Classifier: Categorizing posts and comments
  - Google Sheets: Storing analysis results

## Known pitfalls, handle each one explicitly in your implementation
1. Sentiment analysis can misinterpret technical praise as negative sentiment if the prompt lacks context about Apple's engineering culture.

## Reference implementation
https://n8n.io/workflows/4980 (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/reddit-sentiment-analysis-for-apple-wwdc25/ via usecasesforagents.com