llm-assisted-curation
llm-assisted-curation is a Fine-tuning & training data skill for AI agents, published by mkurman in the zorai repository on GitHub. Skillspace rates llm-assisted-curation D (62/100) and it passed the safety scan; the rating is based on static analysis only.
Use locally-hosted LLMs (vLLM/SGLang) for dataset filtering, quality scoring, rewriting, labeling, and synthetic data generation. Covers LLM-as-judge scoring, structured output filtering, batch inference pipelines, and 2025-2026 techniques (DataRater, perplexity filtering, curriculum scoring, LLM-based dedup).
- Grade
- D
- Quality
- 62 / 100
- Safety
- Passed
- GitHub stars
- 320
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 1 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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