autoresearch-suite

Runs autonomous modify-verify-revert iteration loops against measurable metrics until convergence.

Updated May 29, 2026
One-click install
npx skills add https://github.com/RatnaAtika/Indonesian-ASR-11-Class-Dataset --skill autoresearch-suite-ratnaatika
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: autoresearch-suite
Source: https://github.com/RatnaAtika/Indonesian-ASR-11-Class-Dataset/tree/main/.agents/skills/autoresearch-suite
Command: npx skills add https://github.com/RatnaAtika/Indonesian-ASR-11-Class-Dataset --skill autoresearch-suite-ratnaatika

SYSTEM DOCUMENTATION & REQUIREMENTS

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.

Frequently Asked Questions about autoresearch-suite

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run an autonomous code improvement loop with git?

Define a measurable goal, a scope, and a verify command, then invoke the loop. Each iteration makes one focused change, commits it, runs verification, keeps improvements, and reverts regressions, logging every result until the cap is reached.

What metrics can the autoresearch loop optimize?

Any mechanically verifiable target works: test coverage percentages, benchmark scores, bundle size in kilobytes, p95 latency, lint or type error counts. The verify command must output a comparable number or a pass/fail result.

Does the iteration loop require git history?

Yes. The loop commits before every verification so failed experiments can be reverted with git revert, and it reads git log and git diff before each iteration. Repositories without git history are explicitly unsupported.

Can the loop run indefinitely without stopping?

Only if the user explicitly opts in and can interrupt. By default you set an iteration cap with Iterations: N, which the loop honors strictly to prevent unbounded autonomous changes.

When should I not use an autonomous iteration loop?

Avoid it when no mechanical verification exists or can be defined, and for subjective work like copy tone or visual design without metrics. For subjective refinement, use the reason subcommand with its blind-judge panel instead.

Is the security audit command safe to run automatically?

The security audit is read-only by default, performing STRIDE, OWASP, and red-team analysis without modifying code. The --fix mode that applies changes must never run without explicit user confirmation.