You are helping me build the following AI agent workflow.

## Goal
Auto-classify Lead Intent via Email: Analyzes incoming emails to classify lead intent and stage, then updates your CRM with status changes and tags like high intent.

## Specification
- What it does: You get clearer visibility into your sales pipeline as the agent analyzes incoming emails to classify lead intent and stage. It automatically updates your CRM with the correct status changes and applies relevant tags like high intent based on that analysis.
- Trigger: Triggered by an event (Event · on new email conversation)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - CRM: Storing lead stage and tags
  - LLM: Analyzing email content for intent

## Known pitfalls, handle each one explicitly in your implementation
1. The LLM might misinterpret polite rejection as continued interest so always include explicit negative examples in the prompt.
2. Email threading can cause context overflow if you pass full conversation history so truncate older messages before sending to the model.
3. Ambiguous language like 'maybe later' may not fit standard stages so define a fallback 'needs_review' status in your CRM.

## Reference implementation
https://www.youtube.com/watch?v=79NaG53hCAE (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/auto-classify-lead-intent-via-email/ via usecasesforagents.com