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des-data-source-assessment

Inventory and assess candidate data sources against product requirements and KPIs.

2|Updated May 20, 2026
Search Tags:#data governance#evidence collection#phase handoff#data source inventory#source probing#data quality profiling#freshness assessment
One-click install
npx skills add https://github.com/DKSang/DES-SKILL --skill des-data-source-assessment
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: des-data-source-assessment
Source: https://github.com/DKSang/DES-SKILL/tree/main/skills/des-data-source-assessment
Command: npx skills add https://github.com/DKSang/DES-SKILL --skill des-data-source-assessment

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents data engineering projects from proceeding with unsuitable, inaccessible, unowned, low-quality, or legally risky source systems by creating a rigorous Data Source Inventory and evidence-backed assessment before downstream design starts.

Core Features & Use Cases

  • Source inventory and assessment: Identify and classify candidate source systems (types, generation patterns, ownership, access methods, and evidence).
  • Evidence-driven validation: Capture or reference probe/sample/schema/docs evidence for key sources, and explicitly mark Unknown/Risk/Blocked when evidence is missing.
  • Risk-aware handoff for Phase 06: Produce Phase 05 artifacts (support plan, evidence pack, revision, done gate, and handoff) so domain modeling can safely proceed with clear source-of-truth decisions and constraints.

Quick Start

Use des-data-source-assessment after you have Phase 04 Data Product Specification and the Phase 04-to-05 handoff, to produce _des-output/planning-artifacts/05-data-source-inventory.md with verified source mappings, evidence statuses, and a ready-to-model Phase 05 handoff.

Frequently Asked Questions about des-data-source-assessment

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

FAQPage Schema
What is data source assessment in data engineering workflows?▼

Data source assessment validates candidate source systems by inventorying types, probing schemas, and evaluating ownership, access, quality, and security. This process ensures source systems are accessible, owned, and legally compliant before domain modeling and downstream design begin.

How do I inventory and probe data sources for quality and freshness before modeling?▼

Inventory and probe data sources by capturing schema, sample, and documentation evidence, then assess freshness, quality, and access methods. Explicitly mark unknown, risk, or blocked statuses when evidence is missing to create an evidence-backed source validation plan.

When do I need to validate data source ownership, licensing, and security before domain modeling?▼

Validate data source ownership, licensing, and security prior to domain modeling when source access and legal risks need evidence. This prevents data engineering projects from proceeding with unsuitable, inaccessible, or legally risky source systems during phase handoff.

Can I proceed to downstream design if data source probing reveals missing schema or quality evidence?▼

You should not proceed to downstream design if probing reveals missing schema or quality evidence. Mark these sources as Unknown, Risk, or Blocked, and produce a support plan with clear source-of-truth decisions and constraints before phase handoff.

What's the best way to document data source risks and constraints for phase handoff?▼

Document data source risks by creating a complete inventory with verified source mappings, evidence statuses, and a done gate. Produce evidence-backed handoff artifacts including a support plan and revision log so domain modeling can safely proceed.

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