What problem does it solve? Manually iterating on a measurable target (test coverage, benchmark score, bundle size, latency) is slow and error-prone. This Skill automates the loop: it makes one focused change, commits it, runs a mechanical verification command, keeps improvements, reverts regressions, and repeats until the metric converges or an iteration cap is hit. ## Core Features & Use Cases - Autonomous Iteration Loop: Modify → commit → verify → keep/revert cycles driven by git history and a results log, with strict one-change-per-iteration discipline. - 11 Subcommands: plan (goal wizard), security (STRIDE/OWASP audit), ship (release checklist), debug, fix, scenario, predict, learn, reason, and probe. - Safety Guardrails: Commit-before-verify so failures are revertible, guard commands that must pass, read-only security audits by default, and strict honoring of iteration limits. - Use Case: A team wants to raise test coverage from 72% to 90%. They define the metric and verify command, then let the loop run overnight and review the git log of kept and reverted experiments in the morning. ## Quick Start Ask the agent to run the autoresearch loop with a goal of raising test coverage to 90 percent using the project's test command, capped at 20 iterations.