How do I install the Analyzing Nft Rarity skill?

Run npx skillmds@latest add tools-only/analyzing-nft-rarity-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Analyzing Nft Rarity safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Analyzing Nft Rarity?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Analyzing Nft Rarity free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Analyzing Nft Rarity?

tools-only (@tools-only) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Analyzing Nft Rarity by tools-only — Agent Skill

Name: Analyzing Nft Rarity
Rating: 4.5 (4 reviews)
Author: tools-only

Analyzing Nft Rarity

Calculate NFT rarity scores and rank tokens by trait uniqueness. Use when analyzing NFT collections, checking token rarity, or comparing NFTs. Trigger with phrases like "check NFT rarity", "analyze collection", "rank tokens", "compare NFTs".

tools-only Updated Sep 22, 2026 7 repo stars

File contents

Analyzing NFT Rarity

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 {baseDir}/scripts && python3 rarity_analyzer.py collection boredapeyachtclub

Options:

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

2. Check Specific Token

cd {baseDir}/scripts && python3 rarity_analyzer.py token pudgypenguins 1234

3. Compare Multiple Tokens

cd {baseDir}/scripts && python3 rarity_analyzer.py compare azuki 1234,5678,9012

4. View Trait Distribution

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

5. Export Rankings

JSON:

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

CSV:

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

6. Manage Cache

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

Rarity Algorithms

Algorithm	Description	Best For
`rarity_score`	Sum of 1/frequency (default)	General use, matches rarity.tools
`statistical`	Same as rarity_score	Backward compatibility
`average`	Mean of trait rarities	Balanced scoring
`information`	Entropy-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 {baseDir}/references/errors.md for:

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

Examples

See {baseDir}/references/examples.md for:

Collection analysis workflows
Token comparison
Export and caching
Algorithm comparison

Resources

OpenSea API - Metadata source
Rarity Tools - Reference rankings
IPFS - Decentralized metadata

---name: analyzing-nft-rarity-2description: Calculate NFT rarity scores and rank tokens by trait uniqueness. Use when analyzing NFT collections, checking token rarity, or comparing NFTs. Trigger with phrases like "check NFT rarity", "analyze collection", "rank tokens", "compare NFTs".license: MIT---# Analyzing NFT Rarity## OverviewNFT 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```bashcd {baseDir}/scripts && python3 rarity_analyzer.py collection boredapeyachtclub```Options:- `--limit 500`: Fetch more tokens for analysis- `--top 50`: Show top 50 tokens- `--traits`: Include trait distribution- `--rarest`: Show rarest traits- `--algorithm [statistical|rarity_score|average|information]`### 2. Check Specific Token```bashcd {baseDir}/scripts && python3 rarity_analyzer.py token pudgypenguins 1234```### 3. Compare Multiple Tokens```bashcd {baseDir}/scripts && python3 rarity_analyzer.py compare azuki 1234,5678,9012```### 4. View Trait Distribution```bashcd {baseDir}/scripts && python3 rarity_analyzer.py traits doodles```### 5. Export RankingsJSON:```bashcd {baseDir}/scripts && python3 rarity_analyzer.py export coolcats > rankings.json```CSV:```bashcd {baseDir}/scripts && python3 rarity_analyzer.py export coolcats --format csv > rankings.csv```### 6. Manage Cache```bashcd {baseDir}/scripts && python3 rarity_analyzer.py cache --listcd {baseDir}/scripts && python3 rarity_analyzer.py cache --clear```## Rarity Algorithms| Algorithm | Description | Best For ||-----------|-------------|----------|| `rarity_score` | Sum of 1/frequency (default) | General use, matches rarity.tools || `statistical` | Same as rarity_score | Backward compatibility || `average` | Mean of trait rarities | Balanced scoring || `information` | Entropy-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 CollectionsWorks with any ERC-721/ERC-1155 collection that has:- OpenSea listing- Standard attributes array format- Accessible metadata## Error HandlingSee `{baseDir}/references/errors.md` for:- API rate limiting- IPFS gateway issues- Collection not found- Token ID not found## ExamplesSee `{baseDir}/references/examples.md` for:- Collection analysis workflows- Token comparison- Export and caching- Algorithm comparison## Resources- [OpenSea API](https://docs.opensea.io/reference/api-overview) - Metadata source- [Rarity Tools](https://rarity.tools/) - Reference rankings- [IPFS](https://ipfs.io/) - Decentralized metadata

Frequently asked questions