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llm-evaluationby Seth HobsonDevelopmentGitHub stars: 41.8k

LLM Evaluation skill: what it does and how to install it

Evaluates LLM applications with automated metrics, human review and model comparisons to track quality and catch regressions.

Summary generated from the skill's documentation.

Install

$ npx skills add wshobson/agents --skill llm-evaluation

Run it in a terminal. If your agent is already running, start a new session so it picks the skill up.

About this skill

What it does. Establishes evaluation suites for LLM applications using automated metrics for generation, classification and retrieval, alongside human assessment and LLM-based judging. It can compare models or prompts, check outputs against references or without them, and track results over time.

When to use it. For measuring application quality, validating prompt changes, detecting regressions or investigating unexpected model behaviour.

History

Repo stars

41.8k+1.5k since 5 Oct 2026

Stars are counted for the whole repository, which holds 76 skills.

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Repo stars by day
DateRepo stars
26 Oct 202641,741
25 Oct 202641,668
24 Oct 202641,623
23 Oct 202641,590
22 Oct 202641,533
21 Oct 202641,400
20 Oct 202641,212
19 Oct 202641,081
18 Oct 202640,990
17 Oct 202640,943
16 Oct 202640,891
15 Oct 202640,824
14 Oct 202640,663
13 Oct 202640,579
12 Oct 202640,457
11 Oct 202640,368
10 Oct 202640,319
9 Oct 202640,307
8 Oct 202640,296
7 Oct 202640,267
6 Oct 202640,238
5 Oct 202640,212

Installs

12.8k

Tracking since . A chart appears once there are 7 days of data.

Installs via skills.sh

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