What are the primary success criteria for a pipeline validation?

Success is measured by sub-500ms response times, 100% success rates over 50+ blocks, and verified data persistence within the storage layer.

Why is empirical rate limit testing necessary?

Documented RPC limits often differ significantly from real-world performance; this skill helps you find the true sustainable RPS (Requests Per Second) to prevent 429 errors in production.

How does it prevent data loss in DuckDB?

The skill implements critical patterns such as CHECKPOINT requirements and CHECK constraints to ensure data is persisted and validated before the pipeline continues.

What blockchains does this skill support?

While it includes specific examples for Ethereum, Bitcoin, and Solana, the validation workflow is designed to be chain-agnostic and works with any blockchain RPC provider.

Blockchain Data Pipeline Validation

Name: Blockchain Data Pipeline Validation
Author: terrylica

byterrylica

Web Scraping & Data Collection

Validates blockchain data collection pipelines using a systematic 5-step empirical workflow to ensure data integrity and storage efficiency.

About

This skill provides a test-driven approach to building robust blockchain data collectors by verifying connectivity, schemas, and sustainable RPC rate limits before production deployment. It focuses on integrating with DuckDB using high-performance batch patterns and specific data integrity constraints, helping developers avoid common pitfalls like data loss or rate-limiting bans. By utilizing empirical testing rather than relying on provider documentation, it ensures a gapless data history across networks like Ethereum, Bitcoin, and Solana.

Key Features

Ready-to-use POC templates for various blockchain networks
High-performance DuckDB integration patterns for blockchain metrics
5-step empirical validation workflow for RPC connectivity and schemas
Data integrity verification using CHECK constraints and checkpoints
Sustainable rate limit discovery through real-world stress testing
0 GitHub stars

Use Cases

Validating a new RPC provider's performance and reliability before scaling
Benchmarking DuckDB storage and insertion speeds for large-scale blockchain data
Designing a gapless data collection pipeline for Ethereum or Bitcoin

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add terrylica/gapless-network-data blockchain-data-collection-validation

For use in Claude.ai and ChatGPT

Download Skill

GitHub