engineering/autoresearch-agent/skills/loop/SKILL.md
Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling. Use when the user runs /ar:loop or asks to run an autoresearch experiment continuously on a schedule.
npx skillsauth add alirezarezvani/claude-skills loopInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Start a recurring experiment loop that runs at a user-selected interval.
/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
If no experiment specified, list experiments and let user pick.
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 |
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}
Write to .autoresearch/{domain}/{name}/loop.json:
{
"cron_id": "{id from CronCreate}",
"interval": "{user selection}",
"started": "{ISO timestamp}",
"experiment": "{domain}/{name}"
}
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.
When user runs /ar:loop stop {experiment}:
.autoresearch/{domain}/{name}/loop.json to get the cron IDCronDelete with that IDloop.json/ar:loop to restart. Results persist — the new loop picks up where the old one left off.autoresearch/{domain}/{name}).data-ai
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