Exploring LLM Evaluations
Investigate AI observability evaluations — `hog` (deterministic code-based), `llm_judge` (LLM-prompt-based), and `sentiment` (user-message sentiment). Find existing evaluations, inspect their configuration, run them against specific generations, query individual results, and set up scheduled reports on an evaluation. Use when the user asks to debug why an evaluation is failing, surface common failure modes, compare results across filters, dry-run a Hog evaluator, prototype a new LLM-judge prompt, inspect sentiment classifications, or manage the evaluation lifecycle.
Security AStatic scan found no risk patternsHow grading works ›
From the source SKILL.md
PostHog evaluations score $ai_generation events. Each evaluation is one of three types:
What this skill does
Exploring LLM Evaluations is a community-contributed Claude Code skill in the design-system-ui sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/exploring-llm-evaluations/ and loads when your prompt matches the skill's trigger.
When to invoke it: Use when the user asks to debug why an evaluation is failing, surface common failure modes, compare results across filters, dry-run a Hog evaluator, prototype a new LLM-judge prompt, inspect sentiment classifications, or manage the evaluation lifecycle.
Who uses this skill
The Exploring LLM Evaluations Claude Code skill is built for product managers, product designers, and cross-functional teams planning, shipping, and measuring product features. It's part of ClaudSkills (also referred to as Claude Skills or Claude Code Skills) — the open community-curated registry of 201,000+ SKILL.md files for Anthropic's Claude Code agent and the wider Claude ecosystem (Claude API, Claude Agent SDK).
How to install
Free
Manual install (2 steps)
mkdir -p ~/.claude/skills/exploring-llm-evaluations
curl -L https://claudskills.com/skills/exploring-llm-evaluations/SKILL.md \
-o ~/.claude/skills/exploring-llm-evaluations/SKILL.md
Or just download SKILL.md directly and drop it into ~/.claude/skills/exploring-llm-evaluations/. Claude Code auto-discovers it on next session.
Skills live at ~/.claude/skills/exploring-llm-evaluations/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\exploring-llm-evaluations\SKILL.md on Windows. See the full install guide for step-by-step instructions.
Telegram
📱 Install from your phone or desktop Telegram
Open @claudskills_bot on Telegram, tap Open Desktop App, and the desktop app installs this skill for you. Or share the bot link with a colleague — they get the same one-tap install. Learn more →
Pro
One-click install via the desktop app
The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.
Pro
For the full experience including quality scoring and one-click install features for each skill — upgrade to Pro.
Frequently asked questions
How do I install the Exploring LLM Evaluations Claude Code skill?
Install via the ClaudSkills desktop app (one click) or copy
SKILL.md from the source repository to
~/.claude/skills/exploring-llm-evaluations/SKILL.md and restart Claude Code. Both flows are detailed at
claudskills.com/install/.
What does the Exploring LLM Evaluations skill do?
Investigate AI observability evaluations — `hog` (deterministic code-based), `llm_judge` (LLM-prompt-based), and `sentiment` (user-message sentiment). Find existing evaluations, inspect their configuration, run them against specific generations, query individual results, and set up scheduled reports on an evaluation. Use when the user asks to debug why an evaluation is failing, surface common failure modes, compare results across filters, dry-run a Hog evaluator, prototype a new LLM-judge prompt, inspect sentiment classifications, or manage the evaluation lifecycle.
Is this skill free to install?
Yes. ClaudSkills is an open registry — every skill keeps its source repository's license, and manual install via copy is free. ClaudSkills Pro ($9/mo, $79/yr, or $149 one-time) adds one-click install via the desktop app and a multi-signal Quality Score.
When should I use the Exploring LLM Evaluations skill?
Use Exploring LLM Evaluations when your Claude Code task falls under the Product category — specifically in the design system ui area. Claude Code auto-discovers installed skills and invokes the right one based on the task description, so you can also ask Claude directly (e.g. "use Exploring LLM Evaluations" or describe the task and let Claude pick). Browse related skills at
/category/product/.
What is a Claude Code skill and how does the Exploring LLM Evaluations skill fit in?
A Claude Code skill is a
SKILL.md file that lives under
~/.claude/skills/<name>/ and tells the Claude Code CLI agent how to perform a specific task (instructions, prompts, allowed tools). Skills are auto-discovered at session start. Exploring LLM Evaluations is one of 67,000+ skills indexed in the open ClaudSkills catalog, classified under the Product category. Learn more at
/learn/what-is-a-claude-skill/.
Attribution & license
Cite this skill
If you reference this skill in a blog post, paper, or documentation, you can cite it as:
APA
PostHog. (2026). Exploring LLM Evaluations [Claude Code skill]. ClaudSkills. https://claudskills.com/skills/exploring-llm-evaluations/
BibTeX
@misc{exploring-llm-evaluations-2026,
author = {PostHog},
title = {Exploring LLM Evaluations [Claude Code skill]},
year = {2026},
publisher = {ClaudSkills},
url = {https://claudskills.com/skills/exploring-llm-evaluations/}
}Embed this skill
Promote, attribute, or link this skill from your own README, blog post, or documentation. All three snippets are free to use — no sign-up, no API key. More distribution surfaces →
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Security scan
Grade A · scanned 2026-10-04 — free static scan against the OWASP Agentic Skills Top 10.
No risk patterns were found in any of the ten OWASP-aligned categories. How grading works ›
- ✓ Prompt injection
- ✓ Data exfiltration
- ✓ Supply chain
- ✓ Reverse shell
- ✓ Credentials
- ✓ Execution
- ✓ Filesystem
- ✓ Persistence
- ✓ Obfuscation
- ✓ Network
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[](https://claudskills.com/skills/exploring-llm-evaluations/#security)
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