Imagine a world where improvements to your repositories are delivered automatically each morning. Issues are automatically triaged, CI failures analyzed, documentation maintained, test coverage improved and compliance monitored - all defined via simple markdown files.

GitHub Agentic Workflows deliver this: automated repository agents, running in GitHub Actions, with security-first design principles.

Workflows run with read-only permissions by default. Write operations require explicit approval through sanitized safe outputs (pre-approved GitHub operations), with sandboxed execution, tool allowlisting, and network isolation ensuring AI agents operate within controlled boundaries.

How they work:

1. Write - Create a .md file with your automation instructions in natural language
2. Compile - Run gh aw compile to transform it into a secure GitHub Actions workflow (.lock.yml)
3. Run - GitHub Actions executes your workflow automatically based on your triggers

Here’s a simple workflow that runs daily to create an upbeat status report:

 title-prefix: "[team-status] "
 labels: [report, daily-status]
Create an upbeat daily status report for the team as a GitHub issue.

The gh aw cli converts this into a GitHub Actions Workflow (.yml) that runs an AI agent (Copilot, Claude, Codex, …) in a containerized environment on a schedule or manually.

The AI coding agent reads your repository context, analyzes issues, generates visualizations, and creates reports - all defined in natural language rather than complex code.

Install the extension, add a sample workflow, and trigger your first run - all from the command line in minutes.

Create custom agentic workflows directly from the GitHub web interface using natural language.