finetuning
finetuning is a Fine-tuning & training data skill for AI agents, published by evo-hq in the evo repository on GitHub. Skillspace rates finetuning C (74/100) and it passed the safety scan; the rating is based on static analysis only.
This skill should be used when picking or diagnosing a training move (SFT, LoRA, DPO/KTO/ORPO, RFT, GRPO/PPO/RLOO, RLHF), or when the user mentions fine-tuning, post-training, training recipe, reward design, or weight updates. Decision tree by reward shape, smoke-run gate, three failure diagnostics, five false-progress patterns. Provider recipes and I/O contract in references/.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 1,335
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
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 1 collections
- Scope
- Portable: works in any project. General fine-tuning technique selection; host tooling only briefly referenced
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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