benchmark-qed-autoe
benchmark-qed-autoe is an LLM evaluation & observability skill for AI agents, published by microsoft in the benchmark-qed repository on GitHub. Skillspace rates benchmark-qed-autoe D (60/100) and it passed the safety scan; the rating is based on static analysis only.
Evaluate RAG system outputs using benchmark-qed scoring methods. Use when: running pairwise comparisons, reference-based scoring, assertion-based evaluation (flat or hierarchical), retrieval metrics, or statistical significance tests on RAG outputs. Also use when the user wants to score, compare, or evaluate RAG methods, measure retrieval quality, or run significance tests on benchmark results — even if they don't say "autoe" explicitly.
- Grade
- D
- Quality
- 60 / 100
- Safety
- Passed
- GitHub stars
- 92
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
- 82 / 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
- 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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