You are helping me build the following AI agent workflow.

## Goal
Workout Logger and Analysis: Log workouts via form to get AI-calculated calories, muscle groups, and next-session tips saved to Sheets with Slack and email alerts.

## Specification
- What it does: Log your workouts via a simple form and receive AI-generated insights, calorie estimates, and personalized next-session suggestions. The system automatically structures your data into a training log in Google Sheets while sending you instant notifications via Slack and email with actionable fitness tips.
- Trigger: Triggered by an event (Manual · on form submission)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Google Sheets: Storing workout logs and history
  - Slack: Sending workout notifications
  - Gmail: Emailing summary and tips
  - Google Gemini Chat Model: Parsing exercises and generating analysis

## Known pitfalls, handle each one explicitly in your implementation
1. Google Sheets row appending might fail silently if column headers do not match exactly so verify header alignment in the setup phase.
2. AI calorie estimates vary widely between models so clearly label them as approximations to manage user expectations.

## Reference implementation
https://n8n.io/workflows/13574 (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/ai-workout-logger-and-analysis/ via usecasesforagents.com