You are helping me build the following AI agent workflow.

## Goal
Generate Lessons Learned Reports From Jira Epics: When a Jira Epic is marked Done, the agent compiles tasks and comments to generate an automated Lessons Learned report in Google Docs.

## Specification
- What it does: Get automated Lessons Learned reports in Google Docs as soon as your Jira Epic is marked Done. The agent gathers tasks and comments from Jira Software to create a structured summary without manual effort.
- Trigger: Triggered by an event (Event · on Epic Done status)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Jira Software: Trigger and fetch epic data
  - OpenAI Chat Model: Generate report content
  - Google Docs: Store final report

## Known pitfalls, handle each one explicitly in your implementation
1. Sensitive project details might leak into the LLM prompt, so strip out PII or confidential identifiers before sending data to OpenAI.
2. Google Docs permissions may prevent the script from editing the file, ensure the service account has editor access to the target folder.
3. Long comment threads can exceed token limits, implement a truncation strategy that keeps the most recent or highest-voted comments first.

## Reference implementation
https://n8n.io/workflows/3934 (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/generate-lessons-learned-reports-from-jira-epics/ via usecasesforagents.com