⚒️ Implement AI-ready GitHub issues with CloudCLI and Telegram summaries
⚡ 484 views · ⚒️ Engineering
💡 Pro Tip — If you need GitHub data beyond what the REST API gives you, ScraperNode has a repository scraper that extracts metadata at scale without token rate limits.
Description
Quick overview
This workflow runs nightly at 2:00 AM to find open GitHub issues labeled “ai-ready”, uses CloudCLI to implement each issue and open a pull request against a target branch, comments back on the issue, and sends a run summary to Telegram.
How it works
- Runs every night at 2:00 AM on a schedule.
- Loads the repository, label, base branch, CloudCLI environment URL, and Telegram chat ID from a configuration step.
- Fetches all open GitHub issues in the configured repository that match the configured label.
- Processes the issues one by one and sends each issue title and body to CloudCLI to implement the change, create a branch, and open a pull request against the configured base branch.
- Posts a comment on each GitHub issue noting that CloudCLI opened a pull request and includes the CloudCLI environment link.
- After all issues are processed, sends a Telegram message summarizing the run and listing the issues handled.
Setup
- Add GitHub credentials with permission to read issues and create issue comments, and ensure the configured repo owner and repo name match your repository.
- Add CloudCLI credentials, set the CloudCLI environment ID/URL in the configuration, and provide a GitHub token in the CloudCLI node so it can push branches and open pull requests.
- Add Telegram bot credentials and set your target Telegram chat ID in the configuration.
- Update the configuration values (label and base branch) to match your triage label (for example,
ai-ready) and the branch you want pull requests opened against (for example,main).
🔗 Nodes Used
GitHub, Telegram, Schedule Trigger
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File