autoresearch

Scaffold a skill-improvement workspace with checklist, baseline, and changelog via Python CLI.

18|2|Updated Mar 18, 2026
One-click install
npx skills add https://github.com/Onlyaguest/ViviStableSkills --skill autoresearch-onlyaguest
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: autoresearch
Source: https://github.com/Onlyaguest/ViviStableSkills/tree/main/autoresearch
Command: npx skills add https://github.com/Onlyaguest/ViviStableSkills --skill autoresearch-onlyaguest

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Scaffold and stabilize the process of improving a skill by providing a reproducible workspace with a checklist, baseline, and changelog.

Core Features & Use Cases

  • Provides a structured workflow to initialize a dedicated workspace, define a small yes/no checklist, capture a baseline, and log iterations.
  • Supports deterministic evaluation by enforcing one-change-per-iteration and maintaining an auditable changelog.
  • Suitable for teams aiming for evidence-based skill refinement across domains.

Quick Start

Initialize a dedicated autoresearch workspace with the init command; then use score and log-iteration to document progress.

Frequently Asked Questions about autoresearch

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

FAQPage Schema
How do I create a reproducible skill improvement workflow with a baseline and changelog?▼

To create a reproducible skill improvement workflow, you can initialize a dedicated workspace that provisions a checklist, captures a baseline, and maintains an auditable changelog for tracking iterations.

What is the best way to track measurable skill iterations for an engineering team?▼

The best way to track measurable skill iterations is by enforcing a one-change-per-iteration rule and logging updates in an auditable changelog within a provisioned workspace directory.

How do I set up an auditable changelog and checklist for evidence-based iteration?▼

You set up an auditable changelog and checklist by running a Python-based CLI with init, score, and log-iteration commands to scaffold the workspace and document progress.

Do I need a Python environment to use this skill improvement workspace?▼

Yes, you need a Python environment because the skill requires a Python-based CLI to execute initialization, scoring, and iteration logging for workspace scaffolding.

Can I apply this iteration tracking workflow to any skill domain?▼

Yes, you can apply this iteration tracking workflow to any skill domain, as it supports evidence-based refinement across product and engineering teams using 3-6 yes/no questions.

What limitations exist when using yes/no questions for skill evaluation?▼

A limitation of using yes/no questions for skill evaluation is that deterministic scoring is constrained to 3-6 binary inputs, restricting nuanced qualitative assessment during iteration tracking.