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glebis/claude-skills169 installs

vision-bench

Score and compare images using vision LLMs as judges. YAML-defined criteria presets for 11 use cases (text-to-image, photorealism, document OCR, charts, UI, portrait, product, scientific, invoice, alt-text, artistic style). Supports OpenAI, Anthropic, Gemini, Mistral, and OpenRouter as judge providers. Keys auto-decrypted via SOPS + age.

How do I install this agent skill?

npx skills add https://github.com/glebis/claude-skills --skill vision-bench
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill is safe. It provides a vision LLM benchmarking utility that uses SOPS for secure API key management and interacts with trusted AI provider platforms.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

What does this agent skill do?

Vision Bench — LLM Image Evaluation

Compare images by scoring them with one or more vision LLM judges against structured rubric criteria.

Quick Start

# Install dependencies
pip install pyyaml openai anthropic mistralai

# Score a single image
python bench.py image.png --criteria photorealism --judge gemini-2.5-flash

# Compare two AI-generated images
python bench.py img_a.png img_b.png \
  --criteria text_to_image \
  --prompt "a fox in a snowy forest" \
  --judge gpt-4o

# Multi-judge consensus
python bench.py img.png \
  --criteria portrait \
  --judges gpt-4o gemini-2.5-flash claude-opus-4-5-20251022

# OpenRouter models (any vision-capable model)
python bench.py img_a.png img_b.png \
  --criteria artistic_style \
  --judges "openrouter/meta-llama/llama-4-maverick" "openrouter/mistralai/pixtral-large-2411"

# List all presets
python bench.py --list-presets

# Save report to file
python bench.py img.png --criteria chart_analysis --save report.md

Presets

PresetUse Case
text_to_imageCompare AI image generators (Midjourney, DALL-E, Flux)
photorealismHow convincingly an image looks like a photo
artistic_styleStyle consistency, composition, color harmony
portraitAI-generated portrait quality and realism
product_photoE-commerce product image quality
document_ocrDocument text extraction and layout understanding
chart_analysisChart and data visualization comprehension
invoiceFinancial document field extraction accuracy
ui_screenshotApp/web screenshot understanding
scientificScientific/medical image accuracy
alt_textAccessibility image description quality

Custom criteria: pass any .yaml file as --criteria path/to/my.yaml.

Judge Providers

PrefixProviderExample
gpt-, o1, o3, o4OpenAIgpt-4o
claude-Anthropicclaude-sonnet-4-5-20251022
gemini-Google Geminigemini-2.5-flash
pixtral-, mistral-, ministral-Mistralpixtral-12b-2409
openrouter/OpenRouter (any model)openrouter/meta-llama/llama-4-maverick

API Keys

Keys are loaded from secrets.enc.yaml (SOPS + age encrypted) with fallback to environment variables.

Supported keys: OPENAI_API_KEY, ANTHROPIC_API_KEY, GEMINI_API_KEY, OPENROUTER_API_KEY

To encrypt your own keys:

sops --config .sops.yaml --encrypt --input-type yaml --output-type yaml secrets.yaml > secrets.enc.yaml

Output Formats

--output markdown (default) · --output json · --output table

Files

  • bench.py — CLI entry point
  • judge.py — Multi-provider LLM judge logic
  • report.py — Report generation
  • vault.py — SOPS secrets decryption
  • criteria/ — 11 YAML preset files
  • .sops.yaml — Age key config for encryption
  • secrets.enc.yaml — Encrypted API keys

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/glebis/claude-skills/vision-bench">View vision-bench on skillZs</a>