Build zero-copy Solana programs in Rust with reduced compute unit usage.
npx skills add https://github.com/0xinit/cryptoskills --skill pinocchio
Please help me install this Agent Skill. Skill: pinocchio Source: https://github.com/0xinit/cryptoskills/tree/main/skills/pinocchio Command: npx skills add https://github.com/0xinit/cryptoskills --skill pinocchio
This Skill addresses the high compute unit (CU) costs and larger binary sizes associated with traditional Solana program development frameworks like Anchor, enabling developers to build significantly more performant and cost-effective on-chain applications.
Use the pinocchio skill to scaffold a new Solana program project.
High-intent search queries and answers about installing and using this skill.
Solana smart contracts can reduce compute unit costs by using a zero-copy framework that processes transaction data in-place. This minimizes memory overhead and achieves an 88-95% CU reduction compared to Anchor.
Anchor programs experience high compute usage and large binary sizes due to framework overhead. Switching to a zero-dependency, zero-copy framework processes data in-place, reducing binary size by 40% and cutting CU costs significantly.
Zero-copy processing for Solana programs in Rust processes transaction data in-place without allocating new memory. This minimizes memory overhead and optimizes compute unit usage for high-throughput decentralized applications.
Yes, you can build high-throughput DEXs or order books on Solana without hitting compute limits by using a zero-dependency, zero-copy framework. It dramatically reduces compute unit consumption, optimizing performance for demanding applications.
To scaffold a new Solana program project using a zero-copy framework, use the provided skill to generate the project structure. This enables efficient in-place transaction processing and high-performance on-chain application development.
No, you do not need Anchor dependencies to build optimized Solana programs in Rust. A zero-dependency, zero-copy framework provides significant performance gains and smaller binary sizes without traditional framework overhead.
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