Analyzing NFT Rarity

SkillDev tools

Lets your agent calculate NFT rarity scores and rank tokens by how unique their traits are.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Analyzing NFT Rarity skill

About this capability

'Calculate NFT rarity scores and rank tokens by trait uniqueness.

What this skill tells your AI

The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/analyzing-nft-rarity/SKILL.md and read by ahel’s review.

Overview

NFT rarity analysis skill that:

  • Fetches collection metadata from OpenSea API
  • Parses and normalizes trait attributes
  • Calculates rarity using multiple algorithms
  • Ranks tokens by composite rarity score
  • Exports data in JSON and CSV formats

Prerequisites

  • Python 3.8+ with requests library
  • Optional: OPENSEA_API_KEY for higher rate limits
  • Optional: ALCHEMY_API_KEY for direct metadata fetching

Instructions

1. Analyze a Collection

cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py collection boredapeyachtclub

Options:

  1. --limit 500: Fetch more tokens for analysis
  2. --top 50: Show top 50 tokens
  3. --traits: Include trait distribution
  4. --rarest: Show rarest traits
  5. --algorithm [statistical|rarity_score|average|information]

2. Check Specific Token

cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py token pudgypenguins 1234  # port 1234 - example/test

3. Compare Multiple Tokens

cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py compare azuki 1234,5678,9012  # 5678: 1234: 9012 = configured value

4. View Trait Distribution

cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py traits doodles

5. Export Rankings

JSON:

cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py export coolcats > rankings.json

CSV:

cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py export coolcats --format csv > rankings.csv

6. Manage Cache

cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py cache --list
cd ${CLAUDE_SKILL_DIR}/scripts && python3 rarity_analyzer.py cache --clear

Rarity Algorithms

AlgorithmDescriptionBest For
rarity_scoreSum of 1/frequency (default)General use, matches rarity.tools
statisticalSame as rarity_scoreBackward compatibility
averageMean of trait raritiesBalanced scoring
informationEntropy-based (-log2)Information theory approach

Output

  • Collection Summary: Name, supply, trait types
  • Rankings: Tokens sorted by rarity score with percentile
  • Token Detail: Full trait breakdown with contribution
  • Comparison: Side-by-side trait comparison

Supported Collections

Works with any ERC-721/ERC-1155 collection that has:

  • OpenSea listing
  • Standard attributes array format
  • Accessible metadata

Error Handling

See ${CLAUDE_SKILL_DIR}/references/errors.md for:

  • API rate limiting
  • IPFS gateway issues
  • Collection not found
  • Token ID not found

Examples

See ${CLAUDE_SKILL_DIR}/references/examples.md for:

  • Collection analysis workflows
  • Token comparison
  • Export and caching
  • Algorithm comparison

Resources

Signals

GitHub stars
3k
Forks
396
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
analyzing-nft-rarity
Source
github.com/jeremylongshore/tons-of-skills-marketplace