Vision Bench Skill for Claude

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.

10k tokens

context cost

the whole folder, loaded on every use

files

ships runnable scripts

copies elsewhere

how many repositories repackaged it

337

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

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

What comes with it

35 299 bytes besides the instruction

.claude-plugin/plugin.json

.gitignore

.sops.yaml

bench.py

criteria/alt_text.yaml

criteria/artistic_style.yaml

criteria/chart_analysis.yaml

criteria/document_ocr.yaml

criteria/invoice.yaml

criteria/photorealism.yaml

criteria/portrait.yaml

criteria/product_photo.yaml

criteria/scientific.yaml

criteria/text_to_image.yaml

criteria/ui_screenshot.yaml

judge.py

report.py

requirements.txt

vault.py

The instruction itself

7 sections, as written by the author

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

| Preset | Use Case |

|--------|----------|

| text_to_image | Compare AI image generators (Midjourney, DALL-E, Flux) |

| photorealism | How convincingly an image looks like a photo |

| artistic_style | Style consistency, composition, color harmony |

| portrait | AI-generated portrait quality and realism |

| product_photo | E-commerce product image quality |

| document_ocr | Document text extraction and layout understanding |

| chart_analysis | Chart and data visualization comprehension |

| invoice | Financial document field extraction accuracy |

| ui_screenshot | App/web screenshot understanding |

| scientific | Scientific/medical image accuracy |

| alt_text | Accessibility image description quality |

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

Judge Providers

| Prefix | Provider | Example |

|--------|----------|---------|

| gpt-, o1, o3, o4 | OpenAI | gpt-4o |

| claude- | Anthropic | claude-sonnet-4-5-20251022 |

| gemini- | Google Gemini | gemini-2.5-flash |

| pixtral-, mistral-, ministral- | Mistral | pixtral-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

Other skills for the same job

different authors, same section of the catalogue

Canvas Design

by anthropics

vendor ×13

Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

Publish Markdown articles to X (Twitter) Articles editor with proper formatting. Use when user wants to publish a Markdown file/URL to X Articles, or mentions "publish to X", "post article to Twitter", "X article", or wants help with X Premium article publishing. Handles cover image upload and converts Markdown to rich text automatically.

7k tokens scripts zh

Nanobanana Ppt Skills

by ComeOnOliver

×2

AI-powered PPT generation with document analysis and styled images

Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.

Cell (Cell Press) figure preparation: resolution (300-1000 DPI), formats (TIFF/PDF), RGB color, Avenir/Arial fonts, uppercase panel labels, strict image manipulation policies.

Use when creating, editing, formatting, exporting, or extracting LibreOffice Writer (.odt) documents via UNO, including session-based edits, structured text targets, tables, images, lists, patch workflows, and snapshots.

13k tokens scripts zh

How to use it

Copy the folder

Take glebis/vision-bench from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip. Without those the skill loads but fails at the first command.