You are helping me build the following AI agent workflow.

## Goal
Build Your First AI Data Analyst Chatbot: Chat with your data sources to retrieve information and perform precise calculations using an LLM and calculator tool.

## Specification
- What it does: Chat directly with your Google Sheets or databases to retrieve information and perform precise calculations using an LLM and calculator. You can analyze your data and execute math operations simply by asking questions in a chat interface.
- Trigger: Run manually (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: under an hour
- Tools/services involved:
  - OpenAI Chat Model: LLM reasoning and chat interaction
  - HTTP Request: Retrieving data from external sources or databases
  - Calculator: Performing mathematical operations on retrieved data

## Known pitfalls, handle each one explicitly in your implementation
1. LLMs often make arithmetic errors so always route calculation-heavy queries through the dedicated calculator tool instead of asking the model directly.
2. Sensitive data might be exposed in logs if you do not sanitize PII before sending it to the LLM provider.

## Reference implementation
https://n8n.io/workflows/3050 (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/build-your-first-ai-data-analyst-chatbot/ via usecasesforagents.com