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How the serverless queue fits together
Use one issue per unit of work. Put the task and acceptance criteria in its body, and use labels or issue types to route it or indicate its state. These are conventions for your workflow; GitHub does not enforce a task schema or state machine for coding agents.
A GitHub Actions workflow runs on a schedule or in response to an issue event. Its runner invokes the coding CLI, which inspects the repository and uses gh or the GitHub API to read the issue and report progress. GitHub-hosted runners have GitHub CLI preinstalled. GitHub’s guide demonstrates both scheduled CLI automation and issue-triggered workflows: Using GitHub CLI in workflows.
This removes the need to host a separate scheduler or orchestration service for this setup. It does not remove the need to configure credentials, decide how tasks are claimed, or handle failures.
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Create issues that a script can process
GitHub CLI can create an issue non-interactively by supplying a title and body, and supports additional metadata such as labels, assignees, milestones, projects, issue types, parent issues, and blocking dependencies. A simple task record might contain a concise title, a predictable body format, and a label such as agent-ready.
gh issue create --title "Update the import validation" --body "## Task
...
## Acceptance criteria
- ..." --label agent-readyUse body headings as a readable convention for instructions and acceptance criteria. Use labels or issue types for routing and status, and keep those conventions consistent so scripts can filter reliably. The available creation options are documented in the gh issue create manual.
One recovery detail matters if your create command attaches files: the CLI manual warns that some file uploads can fail even though the issue is created. The command may exit non-zero while printing the new issue URL. Therefore, a failed exit status is not proof that no issue exists; check for the created issue before retrying, or you may create a duplicate.
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Find candidate work from the CLI
gh issue list can filter issues by state, label, assignee, author, issue type, and search query. It can also return selected fields as JSON and apply a jq expression, allowing a workflow to select tasks without scraping the web interface. By default, it lists open issues and fetches up to 30; check the command’s help and configure the limit explicitly if your queue may exceed that default.
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gh issue list --state open --label agent-ready --json number,title,labels,urlUse the fields and filters supported by the installed CLI version, and test the query against the repository’s real issue conventions. The listing options and defaults are described in the gh issue list manual.
Run the coding CLI in GitHub Actions
For a periodic queue scan, configure an Actions schedule; for work initiated by a person, use an issue event. The exact trigger and workflow permissions should match the task: a workflow that only reads issues needs less access than one that comments, edits issues, or pushes code.
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Every workflow step that runs GitHub CLI needs GH_TOKEN set to an authenticated token with sufficient permissions. GitHub-hosted runners include gh, but they do not make authenticated writes safe by default. See GitHub’s GitHub CLI in Actions guidance for workflow examples and token setup.
Alternatively, a script can call the REST API. The issue-creation operation is POST /repos/{owner}/{repo}/issues; API requests use the documented method, headers, parameters, authentication, and API version requirements. GitHub CLI can authenticate and make API calls too. Consult the Create an issue REST API documentation for the endpoint contract. Treat access tokens like passwords and never put them in issue bodies, logs, generated prompts, or public workflow output.
Choose a task-claim strategy before enabling parallel runs
Issues expose task state to people, but the reviewed GitHub documentation does not establish transactional issue updates, uniqueness constraints, locks, or an atomic claim operation. If two scheduled runs overlap—or an issue event and a scheduled run select the same task—both may attempt the same work unless your design prevents it.
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A label such as agent-in-progress can make a claim visible, and an Actions concurrency group can help coordinate runs, but treat these as implementation patterns to validate in your own workflow, not as a documented database guarantee. Decide what happens if a run fails after claiming a task, if a write succeeds but the runner times out, or if the status update is only partly applied. Test retries and duplicate triggers; do not assume exactly-once execution.
Keep a reconciliation path for stale in-progress issues and inspect run logs for failures. A queue built on issues can be suitable when tasks are modest, humans benefit from the visibility, and occasional manual recovery is acceptable. If correctness depends on atomic claims, strict consistency, or a formally defined retry protocol, the cited issue and Actions documentation does not establish those guarantees; evaluate a purpose-built queue or database-backed worker instead.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Consider GitHub Agentic Workflows for an integrated route
GitHub’s current Agentic Workflows documentation describes Markdown workflow sources in .github/workflows/ with YAML frontmatter for triggers, permissions, safe outputs, and engine selection. The Markdown body provides the agent instructions. The workflow is compiled with gh aw compile; commit both the Markdown source and generated .lock.yml file.
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The documented engine choices include Copilot, Anthropic Claude, OpenAI Codex, and Google Gemini. Setup and authentication differ by engine and repository context. The guide describes a built-in GITHUB_TOKEN path for Copilot in organization-owned repositories when organization policy allows it and copilot-requests: write is configured. Personal repositories and third-party engines require a repository secret containing a token or API key. Confirm current provider availability, billing, and organization policy in the GitHub Agentic Workflows documentation.
Agentic Workflows default to read-all permissions and provide safe outputs for bounded operations such as creating issues, comments, or pull requests. Grant only the access the task requires. Review a workflow before asking an agent to commit and push it, then inspect the Actions run; import workflows only from sources you trust and review what they do.
Quick Recap
When this approach is a good fit
- Good fit: repository-scoped tasks, human-readable instructions, visible progress, and work that can tolerate explicit retry and reconciliation procedures.
- Less suitable without additional infrastructure: workloads requiring guaranteed atomic claims, strong database consistency, or assured exactly-once processing across competing workers.
- Operational trade-off: Actions can provide scheduled or event-driven execution without a separately maintained orchestration service, while tokens, permissions, concurrency, retries, and stale tasks remain your responsibility.
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