You are helping me build the following AI agent workflow.

## Goal
Web Scraping & Screenshot Automation: Convert natural language prompts into precise web searches using Firecrawl to scrape data and capture full-page screenshots.

## Specification
- What it does: You turn natural language requests into precise web searches that automatically scrape data and capture full-page screenshots using Firecrawl. You receive structured results with titles, links, content snippets, and images instantly without writing any code.
- Trigger: Run manually (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: under an hour
- Tools/services involved:
  - n8n: Workflow orchestration platform
  - Firecrawl: Web scraping and screenshot capture via API
  - OpenRouter Chat Model: Converting natural language to search queries

## Known pitfalls, handle each one explicitly in your implementation
1. Full-page screenshots consume significant API credits and bandwidth, only request them for high-priority targets to manage costs effectively.
2. Dynamic content loaded via JavaScript might not appear in static HTML snippets, use Firecrawl's browser-based scraping mode for such sites.

## Reference implementation
https://n8n.io/workflows/6343 (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/web-scraping-screenshot-automation/ via usecasesforagents.com