Triage GitHub issues to a Notion board with Qwen via OpenRouter

WHAT IT DOES

When a new issue is opened on a GitHub repository, this workflow uses an AI model to classify it by type (bug, feature, question, documentation, other), assign a priority level (high, medium, low), and generate a one-sentence summary. Results are written to a Notion database and posted as a triage comment on the GitHub issue. No external triage service. No SaaS subscription. Runs on your own n8n instance.

HOW IT WORKS

1. GitHub Webhook Trigger Listens for the "issues" event with action "opened" on the configured repository. Fires only when a new issue is created. Does not trigger on comments, edits, or closes.

2. Extract Issue Data Parses the webhook payload. GitHub Trigger wraps the full payload as a JSON string in the "body" field, so this node extracts the actual issue object, then pulls out the fields the workflow needs: issue number, title, body text (truncated to 2000 characters to stay within LLM token limits), URL, author, labels, and repository full name. Falls back to parsing the repositoryurl field if the repository object is missing from the payload.

3. Duplicate Check (Notion) Queries the Notion database for an existing entry with the same Issue URL. If a match is found, the workflow stops — this issue was already triaged. If the Notion API fails (timeout, rate limit, invalid token), the error branch fires and the workflow continues anyway. A failed duplicate check should not block triage.

4. AI Triage (Qwen 3 via OpenRouter) Sends the issue title and body to the model with a structured prompt that asks for: category, priority, summary, and suggested labels. The prompt includes clear definitions for each category and priority level so the model classifies consistently. If the LLM call fails, a fallback node assigns default values (category: other, priority: medium) so the issue is still tracked in Notion.

5. Create Notion Entry Writes a new row to the Notion database with all triage fields populated: title, issue URL, author, category, priority, summary, suggested labels, status (Open), source (ai or fallback), and creation date.