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gehtalexey
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url-flow

Document LinkedIn URL normalization, Crustdata enrichment, and database storage in SourcingX.

Updated Jan 26, 2026
Search Tags:#debugging#normalization#linkedin#url#enrichment#data matching
One-click install
npx skills add https://github.com/gehtalexey/sourcingX --skill url-flow
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: url-flow
Source: https://github.com/gehtalexey/sourcingX/tree/main/.claude/skills/url-flow
Command: npx skills add https://github.com/gehtalexey/sourcingX --skill url-flow

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a detailed reference for how LinkedIn URLs are processed, normalized, and matched within the SourcingX system, crucial for debugging data inconsistencies and enrichment failures.

Core Features & Use Cases

  • URL Normalization: Understand the steps taken to standardize various LinkedIn URL formats.
  • Enrichment Matching Logic: Learn the multi-tiered strategy used to map incoming URLs to enriched profile data, especially when Crustdata returns different URLs.
  • Database Schema: Reference the relevant database columns (linkedin_url, original_url) and their purpose.
  • Use Case: When the "already enriched" count in SourcingX doesn't match expectations, consult this guide to trace the URL flow and identify potential matching issues.

Quick Start

Consult this documentation when encountering issues with LinkedIn URL matching or data deduplication in SourcingX.

Frequently Asked Questions about url-flow

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

FAQPage Schema
How does LinkedIn URL normalization work for data enrichment?▼

LinkedIn URL normalization standardizes diverse input formats into canonical URLs before API enrichment via Crustdata, ensuring accurate data matching and resolving discrepancies in enrichment counts.

Why does my enrichment count not match the number of LinkedIn URLs processed?▼

Enrichment count discrepancies occur when Crustdata returns different canonical URLs than the input, requiring a multi-tiered matching strategy to map incoming URLs to enriched profile data.

What database schema is used for storing LinkedIn URLs?▼

The database schema uses specific columns including `linkedin_url` for the normalized canonical URL and `original_url` to preserve the initial input, enabling accurate data deduplication and tracing.

How do I debug LinkedIn URL matching failures?▼

Debug LinkedIn URL matching failures by tracing the URL processing pipeline from normalization through Crustdata API enrichment to database storage, identifying where incoming URLs fail to map to enriched profiles.

What is the best way to handle diverse LinkedIn URL formats in data matching?▼

The best way to handle diverse LinkedIn URL formats is implementing a multi-tiered matching strategy that normalizes inputs and maps them to canonical URLs returned by enrichment services.

Can I use this URL normalization process for data deduplication?▼

Yes, the URL normalization process supports data deduplication by standardizing diverse input LinkedIn URLs into canonical formats stored in the database, preventing duplicate profile entries.

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