You are helping me build the following AI agent workflow.

## Goal
Data Analysis & Dashboard Generation: Analyzes engagement data to calculate ROI and LTV trends, then generates an interactive Excel dashboard with recommendations and a...

## Specification
- What it does: You gain clear insights into campaign ROI and customer lifetime value trends through an interactive Excel dashboard that visualizes your engagement data. The agent also provides actionable recommendations and prepares an executive summary presentation for your marketing team to streamline decision-making.
- Trigger: Run manually (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - LLM: Analyze data and generate insights
  - Excel: Create interactive dashboard

## Known pitfalls, handle each one explicitly in your implementation
1. Large datasets can exceed Excel row limits so you must aggregate data before writing to the sheet.
2. Excel formatting styles vary across operating systems so test the generated file on the target platform before distribution.
3. Ambiguous metric definitions can lead to inconsistent ROI calculations so standardize formulas in code rather than relying on LLM logic.

## Reference implementation
https://www.youtube.com/watch?v=USRfRv34HmQ (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/data-analysis-dashboard-generation/ via usecasesforagents.com