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-evaluationRun 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.
Show as a table
| Date | Repo stars |
|---|---|
| 26 Oct 2026 | 41,741 |
| 25 Oct 2026 | 41,668 |
| 24 Oct 2026 | 41,623 |
| 23 Oct 2026 | 41,590 |
| 22 Oct 2026 | 41,533 |
| 21 Oct 2026 | 41,400 |
| 20 Oct 2026 | 41,212 |
| 19 Oct 2026 | 41,081 |
| 18 Oct 2026 | 40,990 |
| 17 Oct 2026 | 40,943 |
| 16 Oct 2026 | 40,891 |
| 15 Oct 2026 | 40,824 |
| 14 Oct 2026 | 40,663 |
| 13 Oct 2026 | 40,579 |
| 12 Oct 2026 | 40,457 |
| 11 Oct 2026 | 40,368 |
| 10 Oct 2026 | 40,319 |
| 9 Oct 2026 | 40,307 |
| 8 Oct 2026 | 40,296 |
| 7 Oct 2026 | 40,267 |
| 6 Oct 2026 | 40,238 |
| 5 Oct 2026 | 40,212 |
Installs
12.8k
Tracking since . A chart appears once there are 7 days of data.
Installs via skills.sh
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