eval-mlflow
eval-mlflow is an LLM evaluation & observability skill for AI agents, published by opendatahub-io in the agent-eval-harness repository on GitHub. Skillspace rates eval-mlflow C (70/100) and it passed the safety scan; the rating is based on static analysis only.
MLflow integration for evaluation — sync datasets, log run results, push/pull feedback between the harness and MLflow traces. Use when the user wants to log eval results to MLflow, sync test cases to MLflow datasets, connect judge scores to traces, pull MLflow annotations for eval-optimize, or view results in the MLflow UI. Triggers on "log to mlflow", "sync dataset", "push results", "mlflow integration", "view in mlflow".
- Grade
- C
- Quality
- 70 / 100
- Safety
- Passed
- GitHub stars
- 34
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
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- 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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