Claude-skill-registry discovery.data_audit
Inventory available datasets, instrumentation gaps, and data quality considerations for the initiative.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/data-audit-edwardmonteiro-aiskillinpractice" ~/.claude/skills/majiayu000-claude-skill-registry-discovery-data-audit && rm -rf "$T"
manifest:
skills/data/data-audit-edwardmonteiro-aiskillinpractice/SKILL.mdsource content
Purpose
Give analytics partners a reusable way to surface the state of data readiness and highlight what is needed to support discovery.
Pre-run Checklist
- ✅ Access existing schema documentation or data dictionaries.
- ✅ Review outstanding data governance tickets or debt.
- ✅ Align with product on the decision timeline and required fidelity.
Invocation Guidance
codex skills run discovery.data_audit \ --vars "domain={{domain}}" \ "decision_goals={{decision_goals}}" \ "current_sources={{current_sources}}" \ "compliance_flags={{compliance_flags}}"
Recommended Input Attachments
- Links to Looker/Mode dashboards or warehouse tables.
- Screenshots of tracking plans or event schemas.
Claude Workflow Outline
- Summarize the decision goals and domain context.
- Produce a data catalog table with source details, owners, freshness, and trust level.
- Identify instrumentation or modeling gaps blocking the decision goals.
- Recommend implementation steps, owners, and sequencing.
- Outline interim proxies or experiments while data gaps are addressed.
Output Template
## Data Inventory | Source | Owner | Freshness | Accessibility | Trust Level | Notes | | --- | --- | --- | --- | --- | --- | ## Gaps & Recommendations 1. Gap — Impact — Suggested Fix — Owner — Timeline ## Decision Support Plan - Immediate next step: - Interim proxy: - Long-term instrumentation:
Follow-up Actions
- File tracking or warehouse work items with clear acceptance criteria.
- Communicate data readiness to product and engineering leadership.
- Schedule follow-up audits post-implementation.