nexus-model-eval
nexus-model-eval is an LLM evaluation & observability skill for AI agents, published by ProfSynapse in the nexus repository on GitHub. Skillspace rates nexus-model-eval F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.
Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.
Grade LLM models on Nexus tool-use (the two-tool getTools/useTools protocol) with the live eval harness in tests/eval/. Use when asked to grade, benchmark, or evaluate one or more OpenRouter (or other provider) models for how well they drive Nexus tools — e.g. "grade google/gemma-4-31b-it" or "benchmark these models on our harness".
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 148
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.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- High-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- references sensitive credential env
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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