evaluating-llms-harness
evaluating-llms-harness is an LLM evaluation & observability skill for AI agents, published by davila7 in the claude-code-templates repository on GitHub. Skillspace rates evaluating-llms-harness 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.
Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 30,694
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
- 94 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- High-risk patterns
- License
- Not declared. Check the repository before reusing it.
What the scanner flagged
- executes shell/subprocess
- dynamic code execution (eval/exec)
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
Also published in 1 other repo
- math-inc/OpenGauss Risky
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.