version: "1.0.1" name: netlify-agent-runner description: Run AI agent tasks remotely on Netlify using Claude, Codex, or Gemini. Use when the user wants to run an AI agent on their site, get a second opinion from another model, or delegate development tasks to run remotely against their repo.

Netlify Agent Runner

Run AI coding agents (Claude, Codex, Gemini) remotely on Netlify infrastructure to automate development tasks on your site.

Prerequisites

• The site must be linked to a Netlify project (via netlify link or netlify init).
• Or skip linking entirely: pass --project <name> (a project ID or name) directly to netlify agents:create to target any Netlify site without linking first.
• The Netlify CLI must be installed and authenticated
• Agent runs consume plan credits. If the account has no available credits — or the agent/AI usage limit has been reached — netlify agents:create is blocked and the run won't start. That's an account/plan-state issue to surface to the user, not something to work around.

Use only documented CLI surfaces

Interact with agent tasks only through the documented netlify agents:* commands (plus netlify --help and the public CLI reference). Do not go around the CLI:

• Do not curl `https://api.netlify.com/...` to fetch, create, or stop a task — the endpoint shapes are not part of the public contract.
• Do not run `netlify api <method>` as a recovery hatch when a documented command fails.
• Do not read auth tokens out of ~/Library/Preferences/netlify/config.json (or anywhere on disk) to authenticate side-channel calls.

If a documented command fails, report the exact error and context to the user and stop — don't invent an undocumented way to reach the task.

How Agent Tasks Run

Read this before creating a task — agent tasks behave differently from running an agent locally, and the differences are easy to miss.

• Remote, not local. Tasks run on Netlify infrastructure, not on your machine. They operate on the site's connected repository, not your local working tree. The remote agent only sees what has been pushed to the remote — it cannot see uncommitted or unpushed changes.
• Branch-based. By default a task runs against the production branch (main or master). To choose a different base branch for the agent to start from, use -b <branch> and make sure that branch has been pushed to the remote first, or the agent will be working from code that doesn't exist remotely. -b sets the base (starting) branch — not where the results are written (see the next bullet).
• Output lands on a new branch — not in place. The agent does not commit its changes onto the base branch you selected. It pushes its work to a new branch with its own Deploy Preview, so your existing branch (or main) is never overwritten. Review the task's results on that new branch / Deploy Preview — don't expect the base branch to change directly.
• Asynchronous. netlify agents:create returns as soon as the task is queued — it does not block until the work is finished. When the command returns, the task is still running remotely.
• No webhooks or callbacks. Nothing notifies you when a task changes state or completes. To find out what's happening, you have to poll with netlify agents:show <task-id> or netlify agents:list.
• Statuses are terminal or not. A task moves through new → running → one of done, error, or cancelled. Keep polling until the status is one of those last three before you act on the results.

Typical workflow

1. Create a task: netlify agents:create "<prompt>" -a <agent>. Note the task ID it returns (use --json to capture it reliably).
2. Poll for status: netlify agents:show <task-id>. Repeat periodically — there is no completion notification — until the status is done, error, or cancelled.
3. Review the results once the task reaches done (or inspect the failure on error).

Creating Agent Tasks

# Run a prompt with the default agent
netlify agents:create "Add a contact form"
 
# Choose a specific agent: claude, codex, or gemini
netlify agents:create --prompt "Add dark mode" --agent claude
netlify agents:create -p "Update the README" -a codex
netlify agents:create -p "Write unit tests" -a gemini
 
# Target a specific branch
netlify agents:create -p "Fix the login bug" -a claude -b feature-branch
 
# Specify a project by name (if not in a linked directory)
netlify agents:create "Add tests" --project my-site-name
 
# Output result as JSON
netlify agents:create "Add a footer" --json

Options

Managing Agent Tasks

All netlify agents:* commands are project-scoped — they operate on a single project (the one your directory is linked to, or the one named with --project <name>), not on your whole team. netlify agents:list shows the tasks for that one project only; there is no team-wide command that lists tasks across all your sites. To see a different site's tasks, run from its linked directory or pass --project <name> for it.

List tasks

# List all tasks for the current site
netlify agents:list
 
# Filter by status
netlify agents:list --status running
netlify agents:list --status done
netlify agents:list --status error
 
# Output as JSON
netlify agents:list --json

Status values: new, running, done, error, cancelled.

Show task details

netlify agents:show <task-id>
netlify agents:show <task-id> --json

Stop a running task

netlify agents:stop <task-id>

Use Cases

Some of the many things you can do with Agent Runners:

Using as an Agent

If you are an AI agent, you can use netlify agents:create to delegate work to an agent running remotely on Netlify — for example, to get a second opinion from a different model.

IMPORTANT — ask for permission first, as a distinct confirmation step. Agent tasks run on Netlify infrastructure and cost the user credits, so a real approval gate matters. Get explicit permission before running any netlify agents:create command — and treat that as its own turn, separate from the user's original request. A directive-sounding prompt ("start a task…", "use the claude agent and pin it to Opus") is not itself the approval: it tells you what they want, but the billable command still waits for a yes.

Make the permission request a concrete proposal, not a menu:

• The exact command, filled in — e.g. netlify agents:create -p "<the real prompt>" -a codex — not a <placeholder> and not a pick-one list of agents.
• One agent, already chosen — commit to a single -a value and say why you picked it ("codex for a second opinion on the auth logic"), rather than offering claude/codex/gemini as interchangeable options.
• Why, plus what happens after "yes": the run is asynchronous — agents:create returns as soon as the task is queued, there's no callback, and you'll poll netlify agents:show <task-id> for the outcome.
• Even if a prerequisite is missing (not authenticated, not linked to a site, not a git repo yet), still show the exact command and chosen agent you'll run once it's resolved — surface the blocker and the concrete proposal, rather than collapsing to only describing the blocker.

Never run these commands without the user's approval.

Before delegating, understand what you're handing off (see How Agent Tasks Run above):

• It runs remotely against the pushed branch — not your local work. The remote agent only sees code that has been committed and pushed. Do not delegate work that depends on your local, in-progress changes; the remote agent can't see them and will work from stale code. If a task needs your current changes, commit and push them first (or finish the work yourself).
• It's asynchronous — delegating does not block you. The task runs remotely while you keep working. But because there are no callbacks, you have to poll (netlify agents:show <task-id>) to learn the outcome. Don't assume the task is done just because you delegated it — check the status before relying on or describing its results.
• It's a separate, self-contained task — not a continuation of your session. The remote agent starts fresh from the repo and the prompt you give it. It has none of your conversation context, so write a complete, standalone prompt.

Useful for:

• Cross-validation — get a second opinion on your implementation from a different model
• Edge case discovery — another model may catch issues you missed
• Alternative approaches — see how a different model would solve the same problem
• Parallel work — kick off an independent task remotely while you continue on other work, then poll for its result