Best NFT rarity tools – check how to assess the value of your tokens

Maciej Zieliński

03 Mar 2022
Best NFT rarity tools – check how to assess the value of your tokens

NFT tokens (Non fungible tokens) are gaining more and more popularity in the new technologies sector. They have spread in almost every area, creating a bridge between the real world and the virtual world. With NFT tokens, their owners have specific rights for certain assets. Unfortunately, many companies decided to use NFT only to achieve profit. What determines their value? What tools can we use to find out whether a given token is worth owning? You can find out in the article below! 

Table of contents

  1. Factors which influence the worth of NFT
  2. Traits, the individual attributes of an NFT
  3. Tools used to evaluate NFT rarity
  5. Icy.Tools
  6. Moby
  7. Traitsniper
  8. Rarytassniffer
  9. What is the difference between NFT and cryptocurrency?
  10. How to purchase NFT?
  11. Fundation
  12. Nifty Gateway
  13. OpenSea
  14. Rarible
  15. SuperRare
  16. What are the dangers involved with purchasing NFT?
  17. Summary
NFT rarity tools

Factors which influence the worth of NFT tokens projects

     It is difficult to determine the precise value of the NFT (non fungible tokens) because this asset class is relatively new. It is worth pointing out that tangible works of art, such as a Rembrandt or physical collectors' items such as NBA player cards, have specific values. In practice, NFT investors wishing to purchase NFT tokens may find it difficult to decide whether a particular form of investment is of interest. To date, many NFT Token products are available on the market. In this respect, fundamental principles have been developed to help establish that NFT carries value. Their attractiveness is determined by the following factors: 

  1. Rarity rank– is an indicator that literally translates into how rare and "difficult to acquire" a specific NFT token is. Good examples of rarity are first of their kind works of art created by a famous digital artist or NFT created by a renowned celebrity. Another factor which indicates rarity is the effect that NFT technology provides in a given sector. 
  2. Usefulness – The usefulness of non fungible tokens results from its actual use, both in the physical and digital world. For example, some NFT are more than collectors' items because they can be used in games to create virtual characters, lands, etc. 

The above-mentioned feature of NFT gives them immediate value, which grows in time. An example of NFT solutionsare Euro 2020 NFT tickets, Collector's Cards such as Geralt of Rivia in the card game “The Witcher Universe Gwent”.

  1. Tangibility – Some NFT are linked to objects in the real world, which also for them to be verified based on their physical characteristics. In principle, anything can be supported by the NFT in order to consolidate ownership rights. However, the value of such an object is determined by its practicality, rarity and personal satisfaction of the users.

Traits, the individual attributes of an NFT 

     Traits are individual features that are an important part of any strategy for the nft rarity of a particular NFT project. When analyzing the various features for given NFT tokens, it is worth considering that it would be a good idea to have at least 150 different attributes. In practice, however, the more diverse the characteristics of a project are, the more unique it will be. Traits can be divided into: 

  1. Feature categories – their main purpose is to help organize all unique features into a specific category. 
  1. Unique features – it is not possible to develop an appropriate rarity strategy for a project without its individual characteristics. Characteristics belong to specific categories. Individual characteristics are an important part of each strategy regarding NFT rarity and are the basis for many related projects. 
  1. Extremely rare features – a set of unique features should always contain rare features. It should be noted that they should not exceed more than 1 percent of the total NFT project volume. 

As you can see, the three basic elements make NFT tokens original. However, specialist rarity tools have been developed to help us evaluate a project. 

NFT rarity tools

NFT rarity tools

Nft rarity can be describe by tools. Below are the new technologies that have received positive reviews from NFT users. The most popular rarity tools for are:

Momentranks makes acquiring NFT tokens easy. This is a great source of accurate NFT token valuations, market tools, sales levels and market capitalization analysis. 


This is a basic tool for tracking NFT. First-time users prefer this solution because of its transparency, simplicity and the ability to quickly analyze the market.


Moby is an unpopular but powerful site that provides real-time data and statistics on multiple NFT tokens. This information can help investors monitor assets and make faster decisions regarding new trends.


Traitsniper is another website that can be used to analyze new NFT projects. With its minimal features, it focuses on analyzing ongoing and upcoming projects and detecting NFT metadata for good investment potential based on their Traits. 


Offers the latest rankings of fresh NFT designs based on their rarity. The rarity tools provides information on the latest NFT collections and historical collection data.

NFT rarity tools

What is the difference between NFT and cryptocurrency?

     NFT collections and cryptocurrency are based on the same technology – blockchain. The NFT markets are shaped in such a way that transactions can be made using cryptocurrency. However, let us remember that cryptocurrency and NFT are completely different products that have been developed for different purposes. Cryptocurrency is a means of payment which is intended to hold a specific value, to be used as exchange goods for other services, etc. NFT tokens can themselves be property and the right to a specific digital commodity. They are closer to a security, or shares, rather than cash. 

NFT space - How to purchase NFT collections?

     You can buy, sell, or trade with NFT. Transactions may take place on exchanges or on specific NFT markets. The creator of a token, or its current owner, determines the token price himself. It is also possible to conduct NFT auctions. In such a case, the bidders will decide on the price. Here are some examples of websites where are nft shop, end where you can purchase NFT or see nft rankings.


It is a market created and managed by the community. Access to it is only possible if you receive an invitation from one of the NFT investors of this market.

Nifty Gateway

It is an art-oriented NFT market. Its main goal is to work with renowned companies, athletes, and artists.


It is one of the most powerful and pioneering sectors where NFT can be found and purchased. It includes a range of collectors' items and there's something here for everyone!


It offers a range of NFT, with art as a priority. The platform created its own token, the RARI, which is used to reward its members for specific activities. 


This place creates a market that offers and at the same time supervises the NFT sector. There are many tokens here that are worthy of attention.

The registration process on each of the above-mentioned platforms may vary from market to market. The basic principle is similar – you buy Non Fungible Token with a cryptocurrency such as ether, although the price can also be stated in dollars. The total cost of the transaction depends on where we buy NFT and at what rate. 

What are the dangers involved with purchasing NFT?

     NFT trading is a technical process that can be misunderstood. As such, some people who want to purchase NFT are unaware that any interaction with blockchain involves fees. In addition, investors must be aware of whether a solid and fair entity is behind the NFT. Otherwise, we may be afraid of losing money. Interestingly, some people buying NFT do this by using bots, as thanks to them their transactions are fast and fully automated. Unfortunately this leads to situations, where new users who wish to purchase NFT may be too late, as they were slower than a robot.  


     NFTs market are modern forms of capital investment in a product, the link between the digital world and the real world. It is worth knowing the rules and tools that will make us more aware of what we want to invest in. The tools used to assess the rarity and the design of Traits will certainly help us with that! We should also remember that, before making an  investment decision, we should familiarize ourselves with the creativity and achievements of the NFT creator, regardless if a single person or an entire team is behind the project.

NFT collection, as well as upcoming NFT projects, are an opportunity for NFT investment. It is important to remember that NFT collectibles should be evaluated on the basis of their rarity rank. The total rarity score of the NFT will show us how interesting and original the project is. NFT investment, purchasing NFT, or NFT drops should be pre-checked and analyzed using NFT tools, global NFT project rankings and NFT news. Afterwards we should run the entire process through NFT analysis based on the NFT we wish to purchase. Let us remember that every project must be checked thoroughly and professionally, as the safety of our finances is paramount.


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Applying Game Theory in Token Design

Kajetan Olas

16 Apr 2024
Applying Game Theory in Token Design

Blockchain technology allows for aligning incentives among network participants by rewarding desired behaviors with tokens.
But there is more to it than simply fostering cooperation. Game theory allows for designing incentive-machines that can't be turned-off and resemble artificial life.

Emergent Optimization

Game theory provides a robust framework for analyzing strategic interactions with mathematical models, which is particularly useful in blockchain environments where multiple stakeholders interact within a set of predefined rules. By applying this framework to token systems, developers can design systems that influence the emergent behaviors of network participants. This ensures the stability and effectiveness of the ecosystem.

Bonding Curves

Bonding curves are tool used in token design to manage the relationship between price and token supply predictably. Essentially, a bonding curve is a mathematical curve that defines the price of a token based on its supply. The more tokens that are bought, the higher the price climbs, and vice versa. This model incentivizes early adoption and can help stabilize a token’s economy over time.

For example, a bonding curve could be designed to slow down price increases after certain milestones are reached, thus preventing speculative bubbles and encouraging steadier, more organic growth.

The Case of Bitcoin

Bitcoin’s design incorporates game theory, most notably through its consensus mechanism of proof-of-work (PoW). Its reward function optimizes for security (hashrate) by optimizing for maximum electricity usage. Therefore, optimizing for its legitimate goal of being secure also inadvertently optimizes for corrupting natural environment. Another emergent outcome of PoW is the creation of mining pools, that increase centralization.

The Paperclip Maximizer and the dangers of blockchain economy

What’s the connection between AI from the story and decentralized economies? Blockchain-based incentive systems also can’t be turned off. This means that if we design an incentive system that optimizes towards a wrong objective, we might be unable to change it. Bitcoin critics argue that the PoW consensus mechanism optimizes toward destroying planet Earth.

Layer 2 Solutions

Layer 2 solutions are built on the understanding that the security provided by this core kernel of certainty can be used as an anchor. This anchor then supports additional economic mechanisms that operate off the blockchain, extending the utility of public blockchains like Ethereum. These mechanisms include state channels, sidechains, or plasma, each offering a way to conduct transactions off-chain while still being able to refer back to the anchored security of the main chain if necessary.

Conceptual Example of State Channels

State channels allow participants to perform numerous transactions off-chain, with the blockchain serving as a backstop in case of disputes or malfeasance.

Consider two players, Alice and Bob, who want to play a game of tic-tac-toe with stakes in Ethereum. The naive approach would be to interact directly with a smart contract for every move, which would be slow and costly. Instead, they can use a state channel for their game.

  1. Opening the Channel: They start by deploying a "Judge" smart contract on Ethereum, which holds the 1 ETH wager. The contract knows the rules of the game and the identities of the players.
  2. Playing the Game: Alice and Bob play the game off-chain by signing each move as transactions, which are exchanged directly between them but not broadcast to the blockchain. Each transaction includes a nonce to ensure moves are kept in order.
  3. Closing the Channel: When the game ends, the final state (i.e., the sequence of moves) is sent to the Judge contract, which pays out the wager to the winner after confirming both parties agree on the outcome.

A threat stronger than the execution

If Bob tries to cheat by submitting an old state where he was winning, Alice can challenge this during a dispute period by submitting a newer signed state. The Judge contract can verify the authenticity and order of these states due to the nonces, ensuring the integrity of the game. Thus, the mere threat of execution (submitting the state to the blockchain and having the fraud exposed) secures the off-chain interactions.

Game Theory in Practice

Understanding the application of game theory within blockchain and token ecosystems requires a structured approach to analyzing how stakeholders interact, defining possible actions they can take, and understanding the causal relationships within the system. This structured analysis helps in creating effective strategies that ensure the system operates as intended.

Stakeholder Analysis

Identifying Stakeholders

The first step in applying game theory effectively is identifying all relevant stakeholders within the ecosystem. This includes direct participants such as users, miners, and developers but also external entities like regulators, potential attackers, and partner organizations. Understanding who the stakeholders are and what their interests and capabilities are is crucial for predicting how they might interact within the system.

Stakeholders in blockchain development for systems engineering

Assessing Incentives and Capabilities

Each stakeholder has different motivations and resources at their disposal. For instance, miners are motivated by block rewards and transaction fees, while users seek fast, secure, and cheap transactions. Clearly defining these incentives helps in predicting how changes to the system’s rules and parameters might influence their behaviors.

Defining Action Space

Possible Actions

The action space encompasses all possible decisions or strategies stakeholders can employ in response to the ecosystem's dynamics. For example, a miner might choose to increase computational power, a user might decide to hold or sell tokens, and a developer might propose changes to the protocol.

Artonomus, Github

Constraints and Opportunities

Understanding the constraints (such as economic costs, technological limitations, and regulatory frameworks) and opportunities (such as new technological advancements or changes in market demand) within which these actions take place is vital. This helps in modeling potential strategies stakeholders might adopt.

Artonomus, Github

Causal Relationships Diagram

Mapping Interactions

Creating a diagram that represents the causal relationships between different actions and outcomes within the ecosystem can illuminate how complex interactions unfold. This diagram helps in identifying which variables influence others and how they do so, making it easier to predict the outcomes of certain actions.

Artonomus, Github

Analyzing Impact

By examining the causal relationships, developers and system designers can identify critical leverage points where small changes could have significant impacts. This analysis is crucial for enhancing system stability and ensuring its efficiency.

Feedback Loops

Understanding feedback loops within a blockchain ecosystem is critical as they can significantly amplify or mitigate the effects of changes within the system. These loops can reinforce or counteract trends, leading to rapid growth or decline.

Reinforcing Loops

Reinforcing loops are feedback mechanisms that amplify the effects of a trend or action. For example, increased adoption of a blockchain platform can lead to more developers creating applications on it, which in turn leads to further adoption. This positive feedback loop can drive rapid growth and success.

Death Spiral

Conversely, a death spiral is a type of reinforcing loop that leads to negative outcomes. An example might be the increasing cost of transaction fees leading to decreased usage of the blockchain, which reduces the incentive for miners to secure the network, further decreasing system performance and user adoption. Identifying potential death spirals early is crucial for maintaining the ecosystem's health.

The Death Spiral: How Terra's Algorithmic Stablecoin Came Crashing Down
the-death-spiral-how-terras-algorithmic-stablecoin-came-crashing-down/, Forbes


The fundamental advantage of token-based systems is being able to reward desired behavior. To capitalize on that possibility, token engineers put careful attention into optimization and designing incentives for long-term growth.


  1. What does game theory contribute to blockchain token design?
    • Game theory optimizes blockchain ecosystems by structuring incentives that reward desired behavior.
  2. How do bonding curves apply game theory to improve token economics?
    • Bonding curves set token pricing that adjusts with supply changes, strategically incentivizing early purchases and penalizing speculation.
  3. What benefits do Layer 2 solutions provide in the context of game theory?
    • Layer 2 solutions leverage game theory, by creating systems where the threat of reporting fraudulent behavior ensures honest participation.

Token Engineering Process

Kajetan Olas

13 Apr 2024
Token Engineering Process

Token Engineering is an emerging field that addresses the systematic design and engineering of blockchain-based tokens. It applies rigorous mathematical methods from the Complex Systems Engineering discipline to tokenomics design.

In this article, we will walk through the Token Engineering Process and break it down into three key stages. Discovery Phase, Design Phase, and Deployment Phase.

Discovery Phase of Token Engineering Process

The first stage of the token engineering process is the Discovery Phase. It focuses on constructing high-level business plans, defining objectives, and identifying problems to be solved. That phase is also the time when token engineers first define key stakeholders in the project.

Defining the Problem

This may seem counterintuitive. Why would we start with the problem when designing tokenomics? Shouldn’t we start with more down-to-earth matters like token supply? The answer is No. Tokens are a medium for creating and exchanging value within a project’s ecosystem. Since crypto projects draw their value from solving problems that can’t be solved through TradFi mechanisms, their tokenomics should reflect that. 

The industry standard, developed by McKinsey & Co. and adapted to token engineering purposes by Outlier Ventures, is structuring the problem through a logic tree, following MECE.
MECE stands for Mutually Exclusive, Collectively Exhaustive. Mutually Exclusive means that problems in the tree should not overlap. Collectively Exhaustive means that the tree should cover all issues.

In practice, the “Problem” should be replaced by a whole problem statement worksheet. The same will hold for some of the boxes.
A commonly used tool for designing these kinds of diagrams is the Miro whiteboard.

Identifying Stakeholders and Value Flows in Token Engineering

This part is about identifying all relevant actors in the ecosystem and how value flows between them. To illustrate what we mean let’s consider an example of NFT marketplace. In its case, relevant actors might be sellers, buyers, NFT creators, and a marketplace owner. Possible value flow when conducting a transaction might be: buyer gets rid of his tokens, seller gets some of them, marketplace owner gets some of them as fees, and NFT creators get some of them as royalties.

Incentive Mechanisms Canvas

The last part of what we consider to be in the Discovery Phase is filling the Incentive Mechanisms Canvas. After successfully identifying value flows in the previous stage, token engineers search for frictions to desired behaviors and point out the undesired behaviors. For example, friction to activity on an NFT marketplace might be respecting royalty fees by marketplace owners since it reduces value flowing to the seller.


Design Phase of Token Engineering Process

The second stage of the Token Engineering Process is the Design Phase in which you make use of high-level descriptions from the previous step to come up with a specific design of the project. This will include everything that can be usually found in crypto whitepapers (e.g. governance mechanisms, incentive mechanisms, token supply, etc). After finishing the design, token engineers should represent the whole value flow and transactional logic on detailed visual diagrams. These diagrams will be a basis for creating mathematical models in the Deployment Phase. 

Token Engineering Artonomous Design Diagram
Artonomous design diagram, source: Artonomous GitHub

Objective Function

Every crypto project has some objective. The objective can consist of many goals, such as decentralization or token price. The objective function is a mathematical function assigning weights to different factors that influence the main objective in the order of their importance. This function will be a reference for machine learning algorithms in the next steps. They will try to find quantitative parameters (e.g. network fees) that maximize the output of this function.
Modified Metcalfe’s Law can serve as an inspiration during that step. It’s a framework for valuing crypto projects, but we believe that after adjustments it can also be used in this context.

Deployment Phase of Token Engineering Process

The Deployment Phase is final, but also the most demanding step in the process. It involves the implementation of machine learning algorithms that test our assumptions and optimize quantitative parameters. Token Engineering draws from Nassim Taleb’s concept of Antifragility and extensively uses feedback loops to make a system that gains from arising shocks.

Agent-based Modelling 

In agent-based modeling, we describe a set of behaviors and goals displayed by each agent participating in the system (this is why previous steps focused so much on describing stakeholders). Each agent is controlled by an autonomous AI and continuously optimizes his strategy. He learns from his experience and can mimic the behavior of other agents if he finds it effective (Reinforced Learning). This approach allows for mimicking real users, who adapt their strategies with time. An example adaptive agent would be a cryptocurrency trader, who changes his trading strategy in response to experiencing a loss of money.

Monte Carlo Simulations

Token Engineers use the Monte Carlo method to simulate the consequences of various possible interactions while taking into account the probability of their occurrence. By running a large number of simulations it’s possible to stress-test the project in multiple scenarios and identify emergent risks.

Testnet Deployment

If possible, it's highly beneficial for projects to extend the testing phase even further by letting real users use the network. Idea is the same as in agent-based testing - continuous optimization based on provided metrics. Furthermore, in case the project considers airdropping its tokens, giving them to early users is a great strategy. Even though part of the activity will be disingenuine and airdrop-oriented, such strategy still works better than most.

Time Duration

Token engineering process may take from as little as 2 weeks to as much as 5 months. It depends on the project category (Layer 1 protocol will require more time, than a simple DApp), and security requirements. For example, a bank issuing its digital token will have a very low risk tolerance.

Required Skills for Token Engineering

Token engineering is a multidisciplinary field and requires a great amount of specialized knowledge. Key knowledge areas are:

  • Systems Engineering
  • Machine Learning
  • Market Research
  • Capital Markets
  • Current trends in Web3
  • Blockchain Engineering
  • Statistics


The token engineering process consists of 3 steps: Discovery Phase, Design Phase, and Deployment Phase. It’s utilized mostly by established blockchain projects, and financial institutions like the International Monetary Fund. Even though it’s a very resource-consuming process, we believe it’s worth it. Projects that went through scrupulous design and testing before launch are much more likely to receive VC funding and be in the 10% of crypto projects that survive the bear market. Going through that process also has a symbolic meaning - it shows that the project is long-term oriented.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.


What does token engineering process look like?

  • Token engineering process is conducted in a 3-step methodical fashion. This includes Discovery Phase, Design Phase, and Deployment Phase. Each of these stages should be tailored to the specific needs of a project.

Is token engineering meant only for big projects?

  • We recommend that even small projects go through a simplified design and optimization process. This increases community's trust and makes sure that the tokenomics doesn't have any obvious flaws.

How long does the token engineering process take?

  • It depends on the project and may range from 2 weeks to 5 months.