Scheduler

Overview

Scheduled jobs are time-based triggers that automatically inject a prompt into the agent's queue at specific times. When a job fires, it creates a queue item with the job's prompt — which is then processed through the normal queue pipeline.

This is different from queue auto processing (configured in the Queue tab), which controls how often the agent processes its queue. Scheduled jobs control what gets added to the queue and when.

Both work together: scheduled jobs add work to the queue, and queue auto processing ensures that work gets picked up.

The Scheduler Tab

The Schedule tab shows all scheduled jobs as a card grid. Each card displays:

• Name — A descriptive label for the job
• Schedule — When it runs (e.g., "Daily at 09:00 Eastern Time")
• Prompt preview — The first two lines of the prompt
• Toggle — Enable or disable the job
• Last run — When the job last fired
• Next run — When it will fire next

Click the ⋮ menu on any card to edit or delete the job.

Creating a Scheduled Job

Click Add Job to open the form drawer:

Name

A descriptive label — e.g., "Morning News Briefing", "Weekly Analytics Report", "Daily Inbox Triage".

Prompt

The message sent to the agent each time the job fires. This is the most important field — see Writing Good Prompts below.

Schedule Type

Time & Timezone

For daily, weekdays, and custom schedules, select the time and timezone. The form auto-detects your browser's timezone as the default.

Day Picker

For custom schedules, click the day buttons to select which days the job should run. At least one day is required.

Model

Choose which AI model the agent uses when processing this job's prompt. Defaults to the latest Claude model.

Writing Good Prompts

When a scheduled job fires, its prompt is injected as a queue item. The agent processes it in a fresh session with no memory of any previous conversation. The prompt must be entirely self-contained.

Good prompt:

Bad prompt:

The agent won't know what "the usual" means in a fresh session. Include:

• What to do — Specific actions and data sources
• Where to deliver — Email address, dataset name, or other output destination
• Format — How results should be structured (bullets, table, summary, etc.)
• Context — Any details the agent needs (locations, preferences, account names)

How Scheduled Jobs Work

Scheduled job fires (e.g., daily at 9am)
  → Prompt injected as a queue item
    → Queue processing picks it up
      → Agent executes in a fresh session
        → Task completed, item marked done

The key insight: scheduled jobs don't run the agent directly. They add items to the queue, which are then processed by the existing queue pipeline. This means:

• Queue auto processing must be enabled for scheduled job items to be picked up
• Multiple scheduled jobs firing close together are processed sequentially
• Each job's queue item gets its own chat session for full traceability

Managing Jobs

Enable / Disable

Use the toggle on each card to pause or resume a job. Disabled jobs don't fire — their schedule is preserved for when you re-enable them.

Edit

Click ⋮ → Edit to modify any aspect of the job — name, prompt, schedule, timezone, or model. If you change the schedule, the next run time is automatically recalculated.

Delete

Click ⋮ → Delete to permanently remove a job.

Via Conversation

Your agent can manage scheduled jobs through the settings_manager tool. Ask it to create, update, list, toggle, or delete jobs conversationally.

Circuit Breaker

If a scheduled job fails 5 consecutive times, the system automatically disables it to prevent wasted resources. When this happens:

• The card shows a yellow warning banner with the failure count and last error
• The toggle shows as disabled
• No further queue items are injected until you re-enable the job

To recover: fix the underlying issue (usually the prompt or a missing credential), then toggle the job back on. Re-enabling resets the failure counter.

Tips & Best Practices

• Test before scheduling — Run the prompt manually first (paste it in chat) to verify the agent produces the expected result. Adjust the prompt based on feedback, then create the scheduled job
• Write self-contained prompts — The agent has no memory between scheduled runs. Include everything it needs in the prompt
• Combine with auto processing — Scheduled jobs add items to the queue; make sure queue auto processing is enabled to pick them up
• Use descriptive names — Good names make the Schedule tab scannable at a glance
• Start with daily — Begin with a daily schedule and adjust frequency once you've validated the output
• Monitor via Runs — Each scheduled job creates a run you can review in the Runs tab
• Check the circuit breaker — If a job stops running, check if it was auto-disabled after failures

What's Next?

• Queue — Understand the queue pipeline that processes scheduled job items
• Runs & Scheduling — View execution history and configure queue processing intervals
• Agent Settings — Configure sandbox, model, and other agent-level settings