Model Evaluator for OpenClaw — Review, Trust Score & Install Guide

Short answer: Model Evaluator is a verified OpenClaw skill for ai & llms. Trust Score 92/100 based on source transparency, permission scope, install safety, update recency, community signal, and documentation quality.

Trust Score: 92/100

Security tier: Verified
Risk level: Low
Last reviewed: 2026-02-17
Reviewer: OpenClaw Skills Hub editorial team
Version: 1.7.0
Author: ml-tools
Install command: npx clawhub@latest install model-evaluator

How we calculate Trust Scores →

What Model Evaluator does

Model Evaluator provides a comprehensive framework for evaluating AI model performance. Run standardized benchmarks, create custom evaluation suites, compare models head-to-head with statistical significance testing, and track quality over time. Supports automated grading with rubrics, human preference collection, and regression detection.

How to install Model Evaluator

Install the OpenClaw CLI: npm install -g clawhub@latest
Install this skill: npx clawhub@latest install model-evaluator
Verify the install: openclaw skills list

Security review

This skill is currently classified as Verified with a low risk profile. Our reviewers inspected the SKILL.md manifest, dependency tree, declared permissions, network calls, and shell commands before publishing this score. See our editorial policy and Trust Score methodology for the full rubric.

Best for

Compare model quality before switching providers
Detect quality regressions after model updates
Validate fine-tuned models against baselines
Run A/B tests with statistical significance

Avoid if

You need a fully air-gapped install with no network calls.
Your environment forbids skills with third-party dependencies.
You require a formally audited SBOM that this version does not yet provide.

Alternatives & related skills

Fine-Tune Studio — Fine-tune open-source models with your data — manage datasets, training runs, and deployments from OpenClaw.
LLM Router — Automatically route prompts to the best model based on task complexity, cost, and latency requirements.
Token Counter — Accurately count tokens for any model, estimate costs, and track usage across all your AI workflows.

Frequently asked questions

What metrics does it track?

Accuracy, fluency, relevance, factuality, latency, cost, and custom rubric scores. All configurable per use case.

Can it evaluate subjective quality?

Yes — it uses LLM-as-judge with configurable rubrics and supports human preference annotation.

How do I install Model Evaluator?

Run `npx clawhub@latest install model-evaluator` from any directory with Claude Code or OpenClaw installed. The skill is added to your local SKILL.md registry and is available to your agent immediately — no restart required.