SkillCheatSheet
evaluating-llms-harness
An AI agent skill from Orchestra-Research/AI-Research-SKILLs, scored 72 out of 100 by code.
Code score by group
It loses the most points in Done criteria (11), the group that checks whether there is a checklist and a step that verifies the work.
What the author says it does
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.
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- Orchestra-Research/AI-Research-SKILLs
- Folder
- 11-evaluation/lm-evaluation-harness
- License
- MIT
- GitHub stars
- 14,480
- SKILL.md lines
- 491
- Other files
- 4
Add evaluating-llms-harness to your agent
npx skills add Orchestra-Research/AI-Research-SKILLs --skill evaluating-llms-harnessThe command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
Labelled for
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Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.