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evaluation-lm-evaluation-harness

An AI agent skill from davila7/claude-code-templates, scored 76 out of 100 by code.

76/ 100B

Code score by group

  • Spec20/20
  • Description13/20
  • Procedure13/15
  • Done criteria4/15
  • Resources9/10
  • Scripts5/8
  • Safety7/7
  • Upkeep5/5

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
davila7/claude-code-templates
Folder
cli-tool/components/skills/ai-research/evaluation-lm-evaluation-harness
License
MIT
GitHub stars
33,382
SKILL.md lines
492
Other files
4

Add evaluation-lm-evaluation-harness to your agent

npx skills add davila7/claude-code-templates --skill evaluation-lm-evaluation-harness

The 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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All skills in davila7/claude-code-templates

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.