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AI搭載のワークフロー自動化でビジネスを変革。エンタープライズのあらゆるニーズを満たす統合プラットフォーム。

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© 2026 ElasticFlow. All rights reserved.

ElasticFlow
HubAll SkillsBy DepartmentBy RoleBy ToolBy MetricMCPsPublishers
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ElasticFlow

AI搭載のワークフロー自動化でビジネスを変革。エンタープライズのあらゆるニーズを満たす統合プラットフォーム。

フォローする

プラットフォーム

  • 機能
  • メリット
  • ユースケース
  • ワークフローライブラリ

ユースケース

  • 営業
  • マーケティング
  • 財務・法務
  • 人事

カタログ

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  • プライバシーポリシー
  • 利用規約
  • Cookieポリシー
  • 許容される利用
  • セキュリティ
  • SLA

© 2026 ElasticFlow. All rights reserved.

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  1. ホーム
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  3. Dashboard Audit
利用可能な言語:🇬🇧 English🇫🇷 Français
AIスキルAudit dashboardProduct & Engineering

Check whether a dashboard can be trusted before a decision. — Claude Skill

Claude Code向けClaudeスキル · 提供:ElasticFlow✓ · 実行:/dashboard-audit(Claude内)·更新日:2026年6月12日·vmanual@2026-06-12

対応GChatGPTClaudeClaudeCCClaude CodeCDClaude DesktopXCodex / Codex CLICursorCursorGeminiGeminiHHermes (via Continue / Cline)OpenClawOpenClawWindsurfWindsurf

Reviews dashboard definitions, freshness, filters, owners, source systems, and obvious contradictions so teams know whether the numbers are safe to use.

  • Explains whether dashboard numbers are decision-ready, stale, inconsistent, or missing context.
  • Checks metric definitions, filters, date ranges, owner, refresh time, source system, and known caveats.
  • Separates cosmetic dashboard issues from problems that can change a business decision.
  • Returns a trust summary, risks, questions for the owner, and fixes to make before sharing.
あなた今日

A team opens a dashboard in a meeting, notices a number looks odd, and spends the discussion arguing about whether it is trustworthy.

/dashboard-audit使用時

Run /dashboard-audit before the meeting to identify stale data, unclear definitions, risky filters, and questions for the owner.

1 Share dashboard context2 Check definitions and freshness3 Flag decision risks4 Ask owner questions

対象ユーザー

Analytics Engineer

Review dashboard trust, definitions, source freshness, and blocking issues.

この役職のスキルを見る
Product Manager

Know whether product metrics are safe for launch or roadmap decisions.

この役職のスキルを見る
Revenue Operations Manager

Check revenue dashboards before forecast, pipeline, or leadership reviews.

この役職のスキルを見る

機能

Leadership dashboard review

Check whether a dashboard is safe to use in a weekly business review.

Metric trust check

Find why numbers look wrong, stale, or inconsistent with another source.

Pre-launch dashboard QA

Review definitions, filters, and owners before a new dashboard goes live.

仕組み

1

Share dashboard screenshots, metric definitions, filters, SQL snippets, or exported numbers.

2

State the decision the dashboard is supposed to support.

3

The skill checks freshness, definitions, filters, source alignment, and contradictions.

4

A human confirms the source owner, fixes blocking issues, and decides whether the dashboard can be used.

入力オプション

Dashboard evidence

Screenshots, exported table, metric definitions, filters, refresh timestamp, or SQL.

例

What the user pastes
Dashboard: Weekly Revenue Overview.
Decision: leadership will decide whether Q3 pipeline recovery plan is working.

Observed:
- Revenue chart says bookings are up 18%.
- CRM report says commit forecast is down 9%.
- Dashboard last refreshed Friday 18:00.
- Filter excludes Enterprise region because of a saved view.
- Owner listed: RevOps Analytics, but owner left last month.

Need: can we use this dashboard in Monday review?
Useful result
Trust level
Do not use as the primary decision source yet. The dashboard may be useful for directional context, but two blocking issues can change the leadership decision.
Blocking issues
Enterprise is excluded by a saved filter, and the owner is stale. Because Enterprise can materially change bookings and forecast, the dashboard is not decision-ready.
Freshness risk
Friday refresh may be acceptable for Monday review only if weekend CRM changes are not material. Confirm refresh schedule and last successful job.
Owner questions
Who owns this dashboard now? Should Enterprise be included? Are bookings and commit forecast intentionally different metrics?
Fix before meeting
Reset filter, assign owner, refresh data, and add a note explaining bookings vs commit forecast.

改善される指標

Data Quality
+10-25%
Product & Engineering
Data Freshness
+15-30%
Product & Engineering
Metric Trust
+25-40%
Product & Engineering

対応ツール

Google Sheets
手動

Review exported numbers, comparison tables, and owner questions.

DataHub
手動

Check ownership, lineage, freshness, and source context.

Snowflake
手動

Verify source freshness, tables, and warehouse-backed data.

SQL
手動

Check definitions and source queries when available.

どこでも使える

スタンドアロン
セットアップ不要

Paste the notes, exports, screenshots, or summaries you already have. The skill works without a connected system.

接続済み
CRM+ツール連携

Connect the relevant support, analytics, CRM, or data tool when you want fresher source evidence.

Dashboard Auditを使ってみますか?

始め方を選択してください。

Claude Codeで実行
無料・オープンソース

このスキルをコンピュータにローカルでインストールして実行します。

1
Claude Codeをインストール

コンピュータでターミナルを開き、このコマンドを貼り付けます:

2
スキルをインストール

GitHubリポジトリを開き、READMEのインストール手順に従ってください。

3
実行する

Claude Codeを起動し、コマンドを入力します:

次に
ElasticFlowで利用
チームとコラボレーション機能

ブラウザからスキルを実行。結果を共有し、アクセス管理、チームで協力。ターミナル不要。

14日間無料トライアル。いつでもキャンセル可能。

Dashboard Audit

Command: /dashboard-audit

When to use it

Reviews dashboard definitions, freshness, filters, owners, source systems, and obvious contradictions so teams know whether the numbers are safe to use.

What the skill produces

  • Explains whether dashboard numbers are decision-ready, stale, inconsistent, or missing context.
  • Checks metric definitions, filters, date ranges, owner, refresh time, source system, and known caveats.
  • Separates cosmetic dashboard issues from problems that can change a business decision.
  • Returns a trust summary, risks, questions for the owner, and fixes to make before sharing.

Inputs to provide

  • Dashboard evidence: Screenshots, exported table, metric definitions, filters, refresh timestamp, or SQL.
  • Decision context: The meeting, business decision, launch, forecast, or review the dashboard supports.
  • Known concerns: Numbers that look wrong, source differences, missing filters, or suspected stale data.

Recommended flow

  1. Share dashboard screenshots, metric definitions, filters, SQL snippets, or exported numbers.
  2. State the decision the dashboard is supposed to support.
  3. The skill checks freshness, definitions, filters, source alignment, and contradictions.
  4. A human confirms the source owner, fixes blocking issues, and decides whether the dashboard can be used.

Useful result example

Trust level

Do not use as the primary decision source yet. The dashboard may be useful for directional context, but two blocking issues can change the leadership decision.

Blocking issues

Enterprise is excluded by a saved filter, and the owner is stale. Because Enterprise can materially change bookings and forecast, the dashboard is not decision-ready.

Freshness risk

Friday refresh may be acceptable for Monday review only if weekend CRM changes are not material. Confirm refresh schedule and last successful job.

Owner questions

Who owns this dashboard now? Should Enterprise be included? Are bookings and commit forecast intentionally different metrics?

Fix before meeting

Reset filter, assign owner, refresh data, and add a note explaining bookings vs commit forecast.

Guardrails

  • Keep user-provided numbers, dates, tool names, commands, IDs, URLs, and rules intact.
  • Do not invent a source, metric, owner, decision, or risk that is not present in the supplied material.
  • Clearly mark what a human must confirm before publishing, changing a tool, or making a business decision.

参照ドキュメント

Dashboard Audit

ElasticFlow editorial instructions for presenting /dashboard-audit in the catalogue.

Purpose

Reviews dashboard definitions, freshness, filters, owners, source systems, and obvious contradictions so teams know whether the numbers are safe to use.

Non-technical presentation

Explain the business problem, what the user provides, what the AI returns, and what a human still needs to confirm. Avoid implementation detail unless the user supplied it.

Catalogue Presentation Method

Every skill should read clearly for a business owner: current painful workflow, better workflow, concrete example, and review checklist.

The page must answer four questions: when to use it, what to provide, what the AI returns, and which human decision remains.

ElasticFlow

AI搭載のワークフロー自動化でビジネスを変革。エンタープライズのあらゆるニーズを満たす統合プラットフォーム。

フォローする

プラットフォーム

  • 機能
  • メリット
  • ユースケース
  • ワークフローライブラリ

ユースケース

  • 営業
  • マーケティング
  • 財務・法務
  • 人事

カタログ

  • 部門
  • ロール
  • ツール
  • メトリクス
  • プラットフォーム

成長

  • 紹介プログラム
  • パートナー

法務

  • プライバシーポリシー
  • 利用規約
  • Cookieポリシー
  • 許容される利用
  • セキュリティ
  • SLA

© 2026 ElasticFlow. All rights reserved.