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lk-data-debug

Identify and fix data-sync issues in LK diagnostic scripts.

Updated Aug 23, 2026
Search Tags:#debug#pagination#timezone#shopify#data-sync#token-audit#lk-intel
One-click install
npx skills add https://github.com/lk-snkrs/spiti-financial-legacy-mixed --skill lk-data-debug
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lk-data-debug
Source: https://github.com/lk-snkrs/spiti-financial-legacy-mixed/tree/main/.hermes/skills/lk/lk-data-debug
Command: npx skills add https://github.com/lk-snkrs/spiti-financial-legacy-mixed --skill lk-data-debug

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams identify and fix subtle data synchronization issues across LK Intel scripts, including time-zone handling, Shopify pagination gaps, token integrity, and schema verification to prevent silent failures.

Core Features & Use Cases

  • Timezone normalization to ensure date comparisons align with the correct timezone and avoid off-by-one errors.
  • Pagination robustness to detect and fix Shopify cursor vs timestamp pagination edge cases.
  • Token audits and schema checks to validate token usage and verify database schemas before ingestion.

Quick Start

Run the LK data debug health checks to surface timezone, pagination, token, and schema issues and initiate the remediation workflow.

Frequently Asked Questions about lk-data-debug

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fix Shopify pagination gaps causing missing data in my sync scripts?▼

Shopify pagination gaps are fixed by detecting cursor versus timestamp edge cases and applying resilience logic to ensure complete data retrieval across sync scripts. This prevents silent data loss during ingestion.

Why does my data sync have timezone off-by-one errors?▼

Timezone off-by-one errors occur during data sync when date comparisons do not align with the correct timezone. Timezone normalization ensures accurate date comparisons and prevents silent data synchronization failures across pipelines.

How do I audit API tokens and verify database schemas before data ingestion?▼

You audit API tokens and verify database schemas by running token integrity checks and proactive schema verification before ingestion. This validates token usage and prevents silent failures across Shopify, Meta, and Klaviyo pipelines.

Does this data debug process work with Meta, Klaviyo, and GA4 pipelines?▼

Yes, the data debug process works with Meta, Klaviyo, and GA4 pipelines. It applies timezone normalization, pagination resilience, token audits, and schema verification across LK data pipelines to ensure accurate and timely data.

What is the best way to prevent silent failures in data synchronization scripts?▼

Preventing silent failures in data synchronization scripts requires implementing robust timezone normalization, cursor pagination resilience, token integrity checks, and proactive schema verification to ensure accurate and timely data ingestion.

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