How does this skill help prevent cryptographic bugs?

It uses an adversarial mindset to identify 'unconstrained columns' or 'selector leakage,' where a malicious prover could satisfy constraints with invalid data, a common source of critical vulnerabilities in ZK systems.

Can this skill help optimize proof performance?

Yes, it provides guidance on degree accounting and auxiliary column usage, helping developers balance prover memory usage against verifier complexity and proof size.

Does it support lookup and permutation arguments?

Absolutely. It includes checklists for grand product arguments, multiset equality, and lookup hygiene to ensure that global consistency checks are soundly implemented.

What is an AIR in zero-knowledge proofs?

AIR stands for Algebraic Intermediate Representation. It is a mathematical framework used primarily in STARKs to represent computations as a set of polynomial constraints over an execution trace.

AIR Cryptographer

Name: AIR Cryptographer
Author: ClementWalter

byClementWalter

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Security & Testing

Provides expert-level guidance for designing, implementing, and auditing Algebraic Intermediate Representations (AIRs) in zero-knowledge proof systems.

This skill equips Claude with specialized knowledge for zero-knowledge cryptography, specifically focusing on STARK-based systems and Algebraic Intermediate Representations (AIRs). It enables deep technical reviews of transition and boundary constraints, polynomial degree accounting, and global consistency arguments like lookups and permutations. By adopting an adversarial 'soundness-first' mindset, the skill helps developers identify vulnerabilities such as unconstrained columns, selector leakage, and Fiat-Shamir hygiene issues, ensuring that proof systems are both performant and mathematically secure.

Key Features

01Verification of global consistency arguments including lookup and permutation proofs

02Detailed polynomial mechanics review including vanishing polynomials and degree accounting

03Expert trace design guidance for optimal column classification and selector discipline

042 GitHub stars

05Adversarial witness analysis to identify soundness loopholes and unconstrained variables

06Fiat-Shamir hygiene checks to ensure secure transcript binding and challenge separation

Use Cases

01Conducting security audits on existing ZK constraint systems to prevent malicious prover exploits

02Optimizing trace layouts and degree behavior to reduce prover memory and verifier costs

03Designing and implementing transition constraints for custom zkVMs or ZK-STARK circuits

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add clementwalter/rookie-marketplace air-expertise

For use in Claude.ai and ChatGPT

Download Skill