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By ArogyaReddy
Autonomously optimize any code file by a measurable Python metric through iterative experiments: set up target file/evaluator/metric, run single iterations or cron-scheduled loops (10min-monthly) that edit code, git commit changes, evaluate, and retain improvements. Resume paused runs, view status dashboard.
Start an autonomous experiment loop with user-selected interval (10min, 1h, daily, weekly, monthly). Uses CronCreate for scheduling.
Resume a paused experiment. Checkout the experiment branch, read results history, continue iterating.
Run a single experiment iteration. Edit the target file, evaluate, keep or discard.
Set up a new autoresearch experiment interactively. Collects domain, target file, eval command, metric, direction, and evaluator.
Show experiment dashboard with results, active loops, and progress.
Uses power tools
Uses Bash, Write, or Edit tools
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