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SkillHub ClubAnalyze Data & AIData / AITesting

evaluate-model

Measure model performance on test datasets. Use when assessing accuracy, precision, recall, and other metrics.

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
785
Hot score
99
Updated
March 20, 2026
Overall rating
C4.6
Composite score
4.6
Best-practice grade
S96.0

Install command

npx @skill-hub/cli install benchflow-ai-skillsbench-evaluate-model

Repository

benchflow-ai/SkillsBench

Skill path: registry/terminal_bench_2.0/full_batch_reviewed/terminal_bench_2_0_train-fasttext/environment/skills/evaluate-model

Measure model performance on test datasets. Use when assessing accuracy, precision, recall, and other metrics.

Open repository

Best for

Primary workflow: Analyze Data & AI.

Technical facets: Data / AI, Testing.

Target audience: Ml teams looking for install-ready agent workflows..

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: benchflow-ai.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install evaluate-model into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/benchflow-ai/SkillsBench before adding evaluate-model to shared team environments
  • Use evaluate-model for ml workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

evaluate-model | SkillHub