ml-engineer
ml-engineer is a Model training & evaluation skill for AI agents, published by brunoamaral in the gregory-ai repository on GitHub. Skillspace rates ml-engineer F (53/100) and it passed the safety scan; the rating is based on static analysis only.
Train, evaluate, debug, and extend GregoryAI's machine learning pipeline for article relevance prediction. Use this skill whenever someone asks about training models, running predictions, debugging ML issues, adding new algorithms, understanding prediction scores, pseudo-labeling, model versioning, or the ML consensus system. Triggers include questions like "train models for team X", "why is recall low", "add a new algorithm", "how does pseudo-labeling work", "run predictions", "check model metrics", "what does the ML pipeline do", or any work involving the gregory.ml module, train_models / predict_articles management commands, or the files_repo_PBL_nsbe research notebooks.
- Grade
- F
- Quality
- 53 / 100
- Safety
- Passed
- GitHub stars
- 56
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
- 80 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
- 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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