What testing methodology does this skill use?

It follows the Branching Tree Technique (BTT), which organizes tests into concrete success paths and revert scenarios based on specific conditions and states.

Does it support testing on live network state?

Yes, it includes specialized rules for fork tests, including vm.createSelectFork patterns and solutions for common token quirks like USDC/USDT blacklists.

Can I use this for production deployments?

Absolutely. It provides standardized patterns for Solidity scripts, including environment variable management, simulation steps, and automated verification commands.

How does this skill improve fuzz testing efficiency?

The skill enforces 'bound before assume' patterns using Foundry's _bound() function, which is significantly more computationally efficient than using vm.assume() for property-based tests.

Foundry Smart Contract Testing

Name: Foundry Smart Contract Testing
Author: sablier-labs

bysablier-labs

•

Security & Testing

Streamlines the creation of robust Foundry-based test suites and deployment scripts for Solidity smart contracts.

About

This skill empowers Claude Code with expert-level knowledge of the Foundry framework to build, debug, and optimize smart contract environments. It implements industry-standard patterns for integration, fuzz, fork, and invariant testing while enforcing the Branching Tree Technique (BTT) for naming and organization. Whether setting up complex stateful property tests or writing deployment scripts with verification, this skill ensures that smart contract code follows rigorous security and gas-efficiency benchmarks modeled after professional DeFi protocols like Sablier.

Key Features

Efficient fuzzer parameter bounding to optimize property-based testing
Automated Branching Tree Technique (BTT) naming and stack modifier patterns
Mainnet state simulation with specialized handling for USDC and USDT tokens
Standardized templates for integration, fuzz, fork, and invariant tests
Production-ready Solidity deployment scripts with verification and broadcasting rules
4 GitHub stars

Use Cases

Developing comprehensive unit and integration tests for complex DeFi protocols
Automating multi-step mainnet deployments and gas-optimized contract initializations
Performing stateful invariant testing to prove protocol-wide security properties

About

Key Features

Efficient fuzzer parameter bounding to optimize property-based testing
Automated Branching Tree Technique (BTT) naming and stack modifier patterns
Mainnet state simulation with specialized handling for USDC and USDT tokens
Standardized templates for integration, fuzz, fork, and invariant tests
Production-ready Solidity deployment scripts with verification and broadcasting rules
4 GitHub stars

Use Cases

Developing comprehensive unit and integration tests for complex DeFi protocols
Automating multi-step mainnet deployments and gas-optimized contract initializations
Performing stateful invariant testing to prove protocol-wide security properties