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You can bring a software-delivery task into GitHub by installing a partner-built agent app from GitHub Marketplace, enabling its agent features, authorizing it, and then calling it from an issue, pull-request comment, or the Agents interface. For implementation work, the agent can investigate a repository, propose and apply changes in a temporary cloud environment, run tests and linters, and open a pull request for a maintainer to review. Agent apps and Agentic Workflows are currently public-preview features, so names, eligibility, and screens can change.
The safest rollout starts with one narrowly defined outcome—such as diagnosing a failing build, preparing a small fix, or checking for a vulnerability—then adds repeatable automation only after permissions and review rules are working.
What are GitHub agent apps?
GitHub agent apps are GitHub Apps that expose partner-built agents inside GitHub. An app developer can supply a custom prompt, model, tools, and Model Context Protocol (MCP) servers, allowing the agent to connect to external systems while you work in a repository. GitHub describes the feature as using partner-built agents directly in GitHub workflows, powered by a Copilot subscription.
Typical uses include analyzing product data, scanning for security vulnerabilities, and adding a feature flag to a pull request. The app is the integration and authorization layer; the agent is the specialist that performs the requested job. Because the feature is in public preview, check the app’s current documentation and permissions before adopting it for a production process.
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Which software-delivery jobs should you give an agent first?
Choose a bounded job with a measurable result and a natural review point. A clear issue or pull request gives the agent context and gives a person a place to inspect its work.
Good first assignments
- Investigate why a specific CI job failed and report the likely cause and evidence.
- Prepare a narrowly scoped code change described in an issue, with tests that demonstrate the intended behavior.
- Scan the repository or a proposed change for a defined class of vulnerability.
- Add or update a feature flag in one pull request.
- Update documentation when the required files and facts are identified in the ticket.
- Check test coverage for a named component and list concrete gaps.
Jobs to postpone
Do not begin with an unbounded request such as “modernize the whole platform,” a production change with no review gate, or a task that depends on credentials the agent is not explicitly allowed to use. Split broad work into issues with a single expected outcome, acceptance criteria, and a test or inspection method.
How do you install and authorize an agent app?
Installation is an account or organization decision, not merely a browser plug-in. The repository owner must install the GitHub App, and the first run normally requires an OAuth authorization.
- Confirm prerequisites. Agent apps are powered by GitHub Copilot and the documented availability is for paid Copilot plans. Verify that the people who will operate the app have the required Copilot access and repository permissions.
- Open GitHub Marketplace. Find the partner’s agent app and read its publisher information, requested permissions, supported repositories, and data-handling terms. Prefer an app whose permissions match the job rather than one requesting broad administrative access.
- Install it for the correct owner. Choose the personal account or organization that owns the target repository, then select which repositories the app can access. If the repository belongs to an enterprise-managed organization, an administrator may first need to enable the enterprise Copilot Agent apps policy.
- Enable agent features. Complete the app’s setup in GitHub and turn on the agent capability if it is presented as a separate option. Record the repositories and permissions selected so they can be reviewed later.
- Authorize on first use. When you invoke the app for the first time, complete the OAuth prompt and inspect the identity, repository scope, and requested actions before accepting. A successful authorization should leave the app available in the issue, pull-request, or Agents interface.
If the app is missing after installation, check that it was installed on the account that owns the repository, that the repository was included in the installation scope, and that the enterprise policy permits agent apps. An administrator can also remove or suspend an app when the integration is no longer needed.
How can you invoke an agent at the point of work?
GitHub provides several entry points. Select the one that gives the right balance of steering, speed, repeatability, and review.
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| Entry point | Best fit | What to provide | Review surface |
|---|---|---|---|
| Issue assignment | A ticket with a defined result and asynchronous progress | Expected outcome, affected area, acceptance criteria, and constraints | Issue updates and any resulting pull request |
| Pull-request comment | Iterative refinement of an existing change | Mention the app and state the exact modification, test, or investigation requested | The existing diff, new commits, and CI checks |
| Agents UI | Exploratory or cross-cutting work | A longer prompt plus repository and scope details | The agent’s response and any branch or pull request it creates |
| GitHub Mobile | Starting or steering the same issue and pull-request tasks away from a desktop | The same concrete instruction you would enter on GitHub.com | Issue or pull-request activity, reviewed in GitHub |
Write an instruction that can be checked
State the desired result, boundaries, and proof. For example: “Investigate the failing integration-tests job on this pull request, identify the first regression in the logs, make no production-code changes, and comment with the failing test and a reproduction command.” For an implementation request, name the files or component when known, describe the behavior, ask for tests, and tell the agent what it must not change.
Keep follow-up requests equally specific. “Update the parser to reject an empty header, add a regression test, run the parser test suite, and explain any unrelated failures” is safer than “fix the remaining issues.”
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What happens when an agent implements a change?
For a well-scoped coding task, GitHub Copilot cloud agent can research the repository, make a plan, create a branch, edit files, run tests and linters in an ephemeral cloud environment, and open a pull request. That automation does not replace maintainership: a person must inspect the diff, interpret CI, and decide whether to merge.
- Research and plan. The agent examines the repository and the issue or pull-request context, then identifies the files and approach it intends to use.
- Change an isolated branch. It works on the existing pull-request branch or on a new branch whose name begins with
copilot/; it cannot push to an arbitrary branch. - Run repository checks. Tests and linters run in the temporary environment available to the agent. Treat the reported results as evidence to verify, not as an approval to merge.
- Open or update a pull request. Use the pull request as the review record. Read the generated explanation, inspect every changed file, and compare the implementation with the acceptance criteria.
- Resolve review and CI findings. Ask for a narrowly defined correction in a pull-request comment or make the change yourself. Re-run required checks after each material update.
- Merge through normal controls. Keep branch protection, required reviewers, and deployment gates in force. A maintainer remains responsible for the final decision.
How do you turn a one-off task into an Agentic Workflow?
Use an Agentic Workflow when the same operation should run from a defined event or schedule—for example, recurring issue triage, CI investigation, status reporting, documentation maintenance, or test-coverage checks. Unlike a conversational invocation, the workflow records its trigger, permissions, tools, and allowed outputs as code.
- Create a Markdown workflow in
.github/workflows/. Put the trigger and the agent instructions in the repository so changes are reviewable. - Declare the operating envelope in frontmatter. Specify when it runs, which permissions it receives, which tools it may use, and which outputs are considered safe. Start with read-only access and add only the output needed for the job.
- Write the instructions in Markdown. Describe the input, decision rules, files or APIs it may inspect, the format of its report, and conditions under which it must stop and ask for human review.
- Compile the workflow. Run the GitHub CLI command below to generate the lock file used for execution.
gh aw compile- Commit both artifacts. Commit the Markdown source and its generated
.lock.ymlfile. Review the diff like any other workflow change. - Run and observe it. Execute it through GitHub Actions or the GitHub CLI, inspect logs and outputs, and tighten the prompt or permissions when a run produces unnecessary work.
Safe outputs are important. A workflow can be allowed to read code and produce a report without being allowed to open issues, post comments, or create pull requests. Declare those write actions explicitly only when they are required and have an appropriate review process.
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Which integration point should your team choose?
Use the task’s operating characteristics rather than choosing an agent because it is the newest interface.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware match| Need | Recommended starting point | Reason |
|---|---|---|
| Close, interactive steering | Local app, CLI, or IDE session | You can inspect intermediate results and redirect the work immediately. |
| A defined task to review later | Cloud agent from an issue or pull request | The agent can work asynchronously and return a branch or pull request. |
| The same operation on a schedule or event | Agentic Workflow in GitHub Actions | The trigger, permissions, tools, and outputs are versioned and repeatable. |
| Exploration across repositories or systems | Agents UI or a carefully scoped app | You can select the agent and provide a longer context before it acts. |
Issue assignment generally provides the most explicit desired result; pull-request comments provide the shortest feedback loop; the Agents UI gives the operator the most room for a cross-cutting prompt; and a workflow gives the highest repeatability. Latency and review surface vary with the task and the app, so measure them with a low-risk pilot instead of assuming one interface is always faster.
What permissions and safety controls should you use?
Least privilege is the default operating model. Read-only repository access is appropriate for investigation and reporting; write access should be tied to a specific output such as a branch, issue comment, or pull request.
- For Agentic Workflows: workflows run in firewalled containers with read-only tokens by default. Writing an issue, comment, or pull request is a safe output that must be declared explicitly.
- For cloud-agent interactions: the user initiating the interaction needs repository write access. A pull-request-triggered Actions run may also require approval from someone with write access.
- For secrets: the cloud agent does not receive ordinary organization or repository Actions secrets. It can use only secrets and variables explicitly added to the
copilotenvironment. - For external systems: inspect the app’s MCP connections and data permissions. Grant access to the systems needed for the bounded job, not to every system your organization owns.
- For lifecycle: review the publisher and permissions periodically. Suspend or uninstall an app that is no longer needed and revoke its authorization when appropriate.
What are the cloud agent’s repository boundaries?
Several limits affect how you design tasks. The cloud agent is limited to the repository where it is creating a pull request. It can push to that pull request’s existing branch or to a new copilot/ branch, but not to an arbitrary branch. Those constraints make a pull request a useful safety boundary: cross-repository changes or release operations need a separate, human-controlled process.
Actions approval and secret handling are separate concerns. A pull request may be created successfully while a later check waits for approval, and a test that depends on an ordinary Actions secret may fail because that secret is not exposed to the agent. Document these prerequisites in the issue so a maintainer can distinguish a code defect from an environment restriction.
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How do you troubleshoot a failed rollout?
The app does not appear
Confirm the installation owner, repository selection, Copilot eligibility, and enterprise Agent apps policy. If the app was recently installed, refresh the repository page and verify that the first-use OAuth authorization completed.
The agent cannot change code
Check whether the initiating user has repository write access, whether the app was installed with the repository included, and whether branch protection or a pending approval is blocking the requested action. A read-only installation can still analyze and report but cannot create the expected branch or pull request.
The workflow posts too much or changes too much
Remove unnecessary write permissions, narrow the trigger, and specify a single safe output. Keep reporting separate from mutation: first run a read-only workflow that proposes an action, then add an explicitly declared write only after the report is reliable.
Tests fail even though the change looks correct
Read the failing log and check whether the test requires a secret, a service, or a setup step unavailable in the cloud environment. Ask the agent to reproduce the failure with a command that does not expose credentials, or reproduce it in your normal CI environment before judging the code.
How should a team roll out agent apps?
Start with one repository and one class of low-risk issue. Define who may install apps, who reviews generated pull requests, which branches are protected, and which outputs an automated workflow may create. Keep a short record of false positives, incomplete fixes, and permission errors from the pilot.
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- Powerful Pass-Through Charging: Supports up to 85W pass-through charging so you can power up your laptop while you use the hub. Note: Pass-through charging requires a charger (not included). Note: To achieve full power for iPad, we recommend using a 45W wall charger.
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Once the team can review results consistently, add a second task with a different risk profile—such as documentation or CI diagnosis—before enabling write-capable automation. Treat every new app, MCP connection, and workflow permission as a separate change to review. Public-preview behavior can change, so revisit the app’s permissions and the GitHub interface after major updates.
What should you do first?
Pick one issue with a clear acceptance test, install an appropriately scoped agent app on only the required repository, authorize it, and invoke it from that issue. Require a human to review the resulting comments, commits, tests, and pull request. After the manual path is dependable, encode the repeatable part as an Agentic Workflow with read-only defaults and explicitly declared safe outputs.
Frequently Asked Questions
Do GitHub agent apps require a separate subscription from Copilot?
GitHub’s documentation describes agent apps as powered by a Copilot subscription and available for paid Copilot plans. The pages do not establish a universal partner-app price, so check the individual publisher’s terms before installation.
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The documented cloud-agent flow creates or updates a pull request; it does not make the maintainer’s merge decision for you. Keep required reviewers, branch protection, and deployment approvals enabled even when an app can write commits.
Are Agentic Workflows the same thing as agent apps?
No. An agent app is an installed GitHub App that exposes a partner agent for interactive use, while an Agentic Workflow is a Markdown-defined, triggerable automation compiled to a lock file and run through Actions or the GitHub CLI. An app can be a component of a broader process, but the two features have different configuration and permission models.
Can I start an agent task from GitHub Mobile?
GitHub Mobile supports the same issue and pull-request entry pattern, so you can assign or mention the app while away from a desktop. For complex changes, review the resulting diff, checks, and permissions on a full repository view before approving anything.
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