qworld-criteria-generation
qworld-criteria-generation is an LLM evaluation & observability skill for AI agents, published by mims-harvard in the Qworld repository on GitHub. Skillspace rates qworld-criteria-generation D (57/100) and it passed the safety scan; the rating is based on static analysis only.
Generate question-specific evaluation criteria using the Qworld Recursive Expansion Tree (RET) algorithm. Decomposes any open-ended question into scenarios, perspectives, and fine-grained binary criteria through structured horizontal and hierarchical expansion. Use when asked to create evaluation rubrics, generate grading criteria, build scoring rubrics for LLM responses, assess answer quality for open-ended questions, or when the user mentions "criteria generation", "evaluation rubrics", "evaluation criteria", "Qworld", or "RET algorithm".
- Grade
- D
- Quality
- 57 / 100
- Safety
- Passed
- GitHub stars
- 30
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
- 80 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
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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