GitHub Copilot app 入门：自动化 Dependabot 拉取请求分类

It’s the perfect task to offload to Copilot! With GitHub Copilot app automations, you can hand off that first round of review. Instead of manually inspecting every Dependabot pull request, you can create an automation that reviews open pull requests, groups them by risk, verifies CI status, and delivers a summary before your day begins.

Follow the steps below to build a daily Dependabot triage automation.

For example, if the summary identifies a major framework upgrade, you can start a new Copilot session from the results and ask Copilot to help complete the migration.

Step 1: Create a new automation

Because the prompt uses natural language, you can customize it to match your team’s workflow.

Turn repetitive work into background work

• Group safe patch updates together
• Separate minor and major version upgrades
• Identify which pull requests have passing CI
• Highlight dependencies that require additional investigation

For example:

I might be biased, but I think Dependabot is pretty amazing. It helps keep my projects up to date, ensuring I’m always using secure libraries. But because there’re frequently new vulnerabilities, there’re frequently new pull requests from Dependabot.

Step 5: Continue the work in a Copilot session

When the automation finishes, Copilot returns a summary instead of a list of individual pull requests.

For recurring maintenance tasks like Dependabot reviews, a daily schedule is often a good choice. For example, you might schedule it to run before your workday begins so the results are waiting when you log in.

You can also choose whether the automation runs in the cloud or on your local machine.

If you want to test it immediately instead of waiting for the scheduled run, choose Create and Run.

If one of the updates requires additional work, you can continue directly from the automation results.

You’ll configure two things first:

If you’re just getting started with automations, begin with a task you already perform on autopilot. Let Copilot handle the routine work so you can spend your time on the decisions that require your expertise.

Ready to automate your next recurring task? Create your first automation in the GitHub Copilot app >

• When it ran
• What actions it performed
• What results it produced

From the GitHub Copilot app, create a new automation.

Once you’ve selected the repository, create the automation.

• Name: Give the automation a descriptive name, such as Daily Dependabot Triage.
• Trigger: Decide when it should run.

Because the session starts with the automation’s context, you don’t have to gather the information again.

Review the open Dependabot pull requests, group them by risk, identify the safe patch and minor version updates, verify that CI is passing for each pull request, and provide a short summary of the recommended next steps.

Step 4: Review the results

• Manual
• Hourly
• Daily
• Weekly
• When an issue is created

Review previous automation runs

Having a history of each run makes automations transparent. You can always review what happened instead of treating them as a black box.

Step 3: Select the repository

Next, tell Copilot what you want it to do.

For example, it might:

Choose the repository or project the automation should analyze.

Step 2: Describe the task in natural language

Available trigger options include:

Rather than interrupting your morning with dozens of small decisions, you can quickly identify which updates are ready to merge and which deserve closer attention.

How can we best triage these pull requests? The work isn’t particularly difficult per se, but it certainly is repetitive.

Dependabot triage is a good example of the kind of recurring task that’s well suited for automation. You describe the workflow once, choose when it should run, and let Copilot perform the repetitive steps automatically.

Sometimes it’s a minor version bump. Sometimes it’s a major version upgrade. Sometimes everything will work just fine. And sometimes… well, every single developer has been caught by a breaking change.

Every automation run is saved, making it easy to see: