skill
evaluating-llms-harness Review findings
orchestra-researchorchestra-research/ai-research-skillsupdated
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.
- Stars
- 14,234
- Version
- v1
- Copies
- 0
Overview
Waxell's checks found 3 findings to review, highest severity high.
- Highest severity
- high
- Findings
- 3
- What ran
- Static analysis
A clean result means nothing alarming in what is published, not a guarantee. How the checks work
We don't republish the skill's instructions. Read them on GitHub at the reviewed commit.
Security
Security scan
Checked 2 days ago
Result
Review findings Waxell's checks found 3 findings to review, highest severity high.
Checked with static analysis: servers it launches, packages it installs at runtime, scripts piped to a shell and bundled binaries. Nothing was run. How the checks work
Findings (3)
high · 3
- high
Tells Claude to install unpinned packages (lm-eval)
SKILL.md:19 · skill_risk:S2
- high
Tells Claude to install unpinned packages (vllm)
SKILL.md:345 · skill_risk:S2
- high
Tells Claude to install unpinned packages (human-eval)
SKILL.md:448 · skill_risk:S2
Versions
Version history
Each distinct content we have seen, newest first, with the verdict it got at the time.
One version so far: v1 (1.0.0), seen 2026-11-03.
See and control which skills your people use
Inside your organization, Waxell scans each skill and plugin before anyone installs it, approves what passes and publishes it to a private marketplace, and puts every MCP tool call behind one governed URL.
30 minutes. No commitment.
SOC 2 Type II attested · ISO/IEC 27001:2022 certified · HIPAA with a BAA · aligned to the EU AI Act and NIST AI RMF
More research skills and plugins
- llama-cpporchestra-researchRuns LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel… No issuesResearchAI & agents14k
- sglangorchestra-researchFast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding,… Review findingsResearchProductivity14k
- tensorrt-llmorchestra-researchOptimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs… No issuesResearchEngineering14k
- mlfloworchestra-researchTrack ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow -… Review findingsResearchEngineering14k