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edwardmonteiro

discoverydata-audit

by edwardmonteiro

Make Claude Skills work in other agents like Codex by adding the missing piece: a small enumerator script.

0🍴 1📅 Dec 23, 2025

SKILL.md


name: discovery.data_audit phase: discovery roles:

  • Data Analyst
  • Analytics Engineer description: Inventory available datasets, instrumentation gaps, and data quality considerations for the initiative. variables: required:
    • name: domain description: Product area or journey requiring data assessment.
    • name: decision_goals description: Business or product decisions the data should support. optional:
    • name: current_sources description: Known data sources or dashboards already leveraged.
    • name: compliance_flags description: Privacy or governance issues to consider. outputs:
  • Data catalog listing sources, owners, freshness, and accessibility.
  • Gap analysis with recommended instrumentation or ETL changes.
  • Alignment summary on how data will support upcoming decisions.

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

  1. Summarize the decision goals and domain context.
  2. Produce a data catalog table with source details, owners, freshness, and trust level.
  3. Identify instrumentation or modeling gaps blocking the decision goals.
  4. Recommend implementation steps, owners, and sequencing.
  5. 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.

Score

Total Score

60/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

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説明文

100文字以上の説明がある

+10
人気

GitHub Stars 100以上

0/15
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3ヶ月以内に更新がある

0/10
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10回以上フォークされている

0/5
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オープンIssueが50未満

+5
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プログラミング言語が設定されている

+5
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1つ以上のタグが設定されている

0/5

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