You are helping me build the following AI agent workflow.

## Goal
Starred Slack Messages to Notion Database...: Every 10 minutes, the agent finds starred Slack messages, generates a title and tags via AI, and saves them to your Notion database.

## Specification
- What it does: Capture important Slack messages instantly by having them organized into your Notion database every ten minutes. You get AI-generated titles and relevant tags for each starred message without any manual sorting.
- Trigger: On a schedule (Scheduled · every 10 minutes)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Slack: Fetching messages and detecting star reactions
  - Notion: Storing archived messages and tags in a database
  - OpenAI Chat Model: Generating titles and categorizing messages with AI

## Known pitfalls, handle each one explicitly in your implementation
1. Notion property types must match the data format exactly, so ensure string tags are converted to multi-select options before creation.
2. LLM outputs can vary in structure, so implement robust error handling and fallback defaults if the model returns malformed JSON.

## Reference implementation
https://n8n.io/workflows/4502 (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/starred-slack-messages-to-notion-database-with-ai/ via usecasesforagents.com