You are helping me build the following AI agent workflow.

## Goal
Meeting Transcript to LinkedIn Content: After a meeting ends, the agent emails you to submit the transcript and brand preferences.

## Specification
- What it does: Get your meeting insights turned into ready-to-post LinkedIn content instantly after you finish a call. Simply email your transcript and brand preferences via Gmail, and the system handles generating and saving your draft in Google Docs for review.
- Trigger: Triggered by an event (Event · on meeting completion)
- Autonomy: You stay in control
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Google Calendar: detecting meeting end
  - Gmail: sending form and notifications
  - Google Docs: storing transcript and content
  - AI Agent: analyzing transcript and generating posts

## Known pitfalls, handle each one explicitly in your implementation
1. Gmail triggers may fire before the meeting actually ends if the calendar status updates early, so add a five-minute delay buffer to ensure accuracy.
2. Long transcripts can exceed token limits for some AI models, so implement a chunking strategy or summarization step before generation.
3. Users might forget to attach the transcript when prompted, so include a clear link to upload it directly in the email body.
4. LinkedIn formatting requires specific line breaks and hashtags, so instruct the AI agent to output raw text that is easy to copy-paste without extra markdown artifacts.

## Reference implementation
https://n8n.io/workflows/7020 (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/meeting-transcript-to-linkedin-content/ via usecasesforagents.com