/ar:loop — Autonomous Experiment Loop

Start a recurring experiment loop that runs at a user-selected interval.

Usage

/ar:loop engineering/api-speed # Start loop (prompts for interval) /ar:loop engineering/api-speed 10m # Every 10 minutes /ar:loop engineering/api-speed 1h # Every hour /ar:loop engineering/api-speed daily # Daily at ~9am /ar:loop engineering/api-speed weekly # Weekly on Monday ~9am /ar:loop engineering/api-speed monthly # Monthly on 1st ~9am /ar:loop stop engineering/api-speed # Stop an active loop

What It Does

Step 1: Resolve experiment

If no experiment specified, list experiments and let user pick.

Step 2: Select interval

If interval not provided as argument, present options:

Select loop interval:

1. Every 10 minutes (rapid — stay and watch)
2. Every hour (background — check back later)
3. Daily at ~9am (overnight experiments)
4. Weekly on Monday (long-running experiments)
5. Monthly on 1st (slow experiments)

Map to cron expressions:

Interval Cron Expression Shorthand

10 minutes */10 * * * *

10m

1 hour 7 * * * *

1h

Daily 57 8 * * *

daily

Weekly 57 8 * * 1

weekly

Monthly 57 8 1 * *

monthly

Step 3: Create the recurring job

Use CronCreate with this prompt (fill in the experiment details):

You are running autoresearch experiment "{domain}/{name}".

1. Read .autoresearch/{domain}/{name}/config.cfg for: target, evaluate_cmd, metric, metric_direction
2. Read .autoresearch/{domain}/{name}/program.md for strategy and constraints
3. Read .autoresearch/{domain}/{name}/results.tsv for experiment history
4. Run: git checkout autoresearch/{domain}/{name}

Then do exactly ONE iteration:

• Review results.tsv: what worked, what failed, what hasn't been tried
• Edit the target file with ONE change (strategy escalation based on run count)
• Commit: git add {target} && git commit -m "experiment: {description}"
• Evaluate: python {skill_path}/scripts/run_experiment.py --experiment {domain}/{name} --single
• Read the output (KEEP/DISCARD/CRASH)

Rules:

• ONE change per experiment
• NEVER modify the evaluator
• If 5 consecutive crashes in results.tsv, delete this cron job (CronDelete) and alert
• After every 10 experiments, update Strategy section of program.md

Current best metric: {read from results.tsv or "no baseline yet"} Total experiments so far: {count from results.tsv}

Step 4: Store loop metadata

Write to .autoresearch/{domain}/{name}/loop.json :

{ "cron_id": "{id from CronCreate}", "interval": "{user selection}", "started": "{ISO timestamp}", "experiment": "{domain}/{name}" }

Step 5: Confirm to user

Loop started for {domain}/{name} Interval: {interval description} Cron ID: {id} Auto-expires: 3 days (CronCreate limit)

To check progress: /ar:status To stop the loop: /ar:loop stop {domain}/{name}

Note: Recurring jobs auto-expire after 3 days. Run /ar:loop again to restart after expiry.

Stopping a Loop

When user runs /ar:loop stop {experiment} :

• Read .autoresearch/{domain}/{name}/loop.json to get the cron ID

• Call CronDelete with that ID

• Delete loop.json

• Confirm: "Loop stopped for {experiment}. {n} experiments completed."

Important Limitations

• 3-day auto-expiry: CronCreate jobs expire after 3 days. For longer experiments, the user must re-run /ar:loop to restart. Results persist — the new loop picks up where the old one left off.

• One loop per experiment: Don't start multiple loops for the same experiment.

• Concurrent experiments: Multiple experiments can loop simultaneously ONLY if they're on different git branches (which they are by default — each experiment gets autoresearch/{domain}/{name} ).