autoresearch
autoresearch is an Execution & autonomous loops skill for AI agents, published by maragudk in the fabrik repository on GitHub. Skillspace rates autoresearch C (74/100) and it passed the safety scan; the rating is based on static analysis only.
Autonomous experiment loop that iteratively improves a measurable metric. Given a goal, a verify command, and an optional guard, the agent branches, makes one change, measures the result, and keeps or discards the experiment -- repeating indefinitely. Use this skill when the user wants to optimize something measurable through automated experimentation, autonomous improvement loops, or when they mention "autoresearch". Works for any domain with a quantifiable metric (code performance, ML training, build size, test scores, content quality metrics, etc.).
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 25
Unproven: rated by static analysis only, not yet compared head-to-head.
Not launch-quality. It is graded C with a clean safety verdict, but our quality filters exclude it: it is a near-duplicate variant of another skill. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 1 other repositories, in 0 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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