Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
LLM Evaluator Pro
LLM-as-a-Judge evaluator via Langfuse. Scores traces on relevance, accuracy, hallucination, and helpfulness using GPT-5-nano as judge. Supports single trace...
skill openclawclawhub Free
LLM-as-a-Judge evaluator via Langfuse. Scores traces on relevance, accuracy, hallucination, and helpfulness using GPT-5-nano as judge. Supports single trace...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/evaluator.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- aiwithabidi
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
LLM Evaluator βοΈ
LLM-as-a-Judge evaluation system powered by Langfuse. Uses GPT-5-nano to score AI outputs.
When to Use
Evaluating quality of search results or AI responses Scoring traces for relevance, accuracy, hallucination detection Batch scoring recent unscored traces Quality assurance on agent outputs
Usage
# Test with sample cases python3 {baseDir}/scripts/evaluator.py test # Score a specific Langfuse trace python3 {baseDir}/scripts/evaluator.py score <trace_id> # Score with specific evaluator only python3 {baseDir}/scripts/evaluator.py score <trace_id> --evaluators relevance # Backfill scores on recent unscored traces python3 {baseDir}/scripts/evaluator.py backfill --limit 20
Evaluators
EvaluatorMeasuresScalerelevanceResponse relevance to query0β1accuracyFactual correctness0β1hallucinationMade-up information detection0β1helpfulnessOverall usefulness0β1
Credits
Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents. π Need help setting up OpenClaw for your business? Book a free consultation
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/evaluator.py