evaluation-methodology
by community
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Description
# Evaluation methodology PluginEval scores a skill or a plugin from 0 to 100 by combining up to three layers. The static layer is a lint. It's fast and deterministic, and it's useful for checking structure. The LLM judge and Monte Carlo layers are experimental, not validated against human labels, so treat their numbers as rough signals. For the trace-based eval program, see `evals/README.md` at the repository root. The judge rubric anchors are in [references/rubrics.md](references/rubrics.md). Fixes for eac
Install evaluation-methodology
Run this in your OpenClaw agent to add evaluation-methodology from the ClawHub registry.
openclaw skills install evaluation-methodologyRequires ClawHub registry access. Review the security analysis below before installing.
Security Analysis
Open Source
Code is publicly available for audit.
Community Verified
Reviewed by the ClawHub community.
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Real user ratings only — separate from the editorial assessment and ClawHub signal.
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Frequently asked questions
Is evaluation-methodology safe to install?
evaluation-methodology has a SkillsReview security score of 50/100. It is open source and community-verified on ClawHub. Check the full Security Analysis on this page before installing.
How much does evaluation-methodology cost?
evaluation-methodology is free to install for OpenClaw via ClawHub.
What are the best alternatives to evaluation-methodology?
You can compare evaluation-methodology side by side with similar OpenClaw skills on the SkillsReview comparison page to find the best fit for your workflow.
How do I install evaluation-methodology?
Install evaluation-methodology from ClawHub at clawhub.ai/skills/evaluation-methodology, or use the install action on this page to copy the command for your OpenClaw agent.
Community Signal
Historical movement
Timeline plus trend snapshots for security, reviews, and reputation tilt.
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