autoresearch
autoresearch is an LLM evaluation & observability skill for AI agents, published by zrosenfield in the sharepoint-ai-skills repository on GitHub. Skillspace rates autoresearch D (65/100) and it passed the safety scan; the rating is based on static analysis only.
Optimize any AI in SharePoint skill by iteratively running it against test inputs, scoring outputs with binary evals, mutating the prompt to fix failures, and keeping improvements. Adapts Karpathy's autoresearch methodology to AI in SharePoint's multi-turn conversation architecture.
- Grade
- D
- Quality
- 65 / 100
- Safety
- Passed
- GitHub stars
- 73
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 91 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
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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