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Claude Code
Cursor
Codex CLI
Muse
Dots+22 moreClaude CodeCursorCodex CLIMuseDots
OpenClaw
Manus
Grok
Grok Bot+18 agentsAI Data Intelligence Command Center™
Turn raw business data into validated analysis, automated dashboards, insights, and decision-ready reports.
$14.99
AI Data Intelligence Command Center™
Example session with this skill installed
Analyze the sales data in ./data/sales.xlsx and create the complete analytics package.
I want you to
- Profile and clean the data.
- Detect duplicates, missing values, invalid values, and suspicious outliers.
- Create a data-quality report.
- Build a reusable data model and data dictionary.
- Calculate revenue, orders, AOV, growth, product, region, and customer KPIs.
- Analyze monthly and yearly trends.
- Identify anomalies and explain their possible causes.
- Create a forecast if there is enough historical data.
- Generate the SQL needed for the main analysis.
- Use Python for deeper analysis where useful.
- Create a professional Excel analytics workbook.
- Create a customizable interactive dashboard.
- Create a Power BI-ready model with DAX measures.
- Create a Tableau-ready dashboard specification.
- Create an executive summary with the 5 most important business findings.
- Create an action plan based only on evidence from the data.
Important rules
- Do not silently delete questionable business records.
- Clearly identify every detected data error.
- Show which numbers are verified and which are estimates.
- If the data has a critical problem, flag it before publishing the final dashboard.
- Keep the dashboard design specific to the business objective rather than using a generic template.
- Preserve an audit trail of important transformations.
At the end, give me:
FINAL DATA QUALITY SCORE
KEY FINDINGS
KEY ERRORS
KPI SUMMARY
DASHBOARD STATUS
FORECAST STATUS
RECOMMENDED ACTIONS
FILES CREATED
LIMITATIONS
- Read your context and instructions
- Compiled the ai data intelligence
AI DATA INTELLIGENCE COMMAND CENTER™
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ANALYTICS STATUS: COMPLETED WITH WARNINGS
DATA QUALITY SCORE: 92/100
DASHBOARD STATUS: PUBLISHED
DATA VALIDATION: PASSED
CRITICAL ERRORS: 0
WARNINGS: 3
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- DATA PROFILE
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Source
sales.xlsx
Rows
184,291
Columns
37
Date range
Jan 2025 – Aug 2026
Duplicate rows
344
Missing-value issues
3
Suspicious records
143
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
2. DATA CLEANING
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✓ Standardized date formats
✓ Normalized category labels
✓ Removed exact duplicate records
✓ Standardized currency fields
✓ Preserved suspicious business outliers for review
Records modified
2,811
Records removed
344 exact duplicates
Business records automatically deleted
0
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
3. DATA WARNINGS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠ WARNING #01
Column
Customer_Region
Issue
2.8% missing
Impact
Regional analysis may undercount affected records.
Status
FLAGGED
⚠ WARNING #02
Column
Revenue
Issue
143 extreme values
Status
RETAINED FOR REVIEW
Reason
Anomaly detection cannot determine whether these are
errors or legitimate high-value transactions.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
4. KPI SUMMARY
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Revenue
$4.82M
Orders
138,420
AOV
$34.82
Revenue Growth
+18.4%
Orders Growth
+11.2%
AOV Growth
+6.5%
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
5. KEY TRENDS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
01
Revenue increased 18.4%.
Primary observed driver
Premium category growth.
02
Orders increased 11.2%.
03
AOV increased 6.5%.
04
West-region revenue declined 8.7%.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
6. ANOMALIES
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🚨 West Region
Revenue
-8.7%
Compared with
Previous comparable period
Severity
MEDIUM
Recommended investigation
Check inventory, traffic, and payment data.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
7. FORECAST
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Forecast generated
YES
Reason
Sufficient historical observations available.
Forecast
$5.03M next period
Confidence
MODEL-DEPENDENT ESTIMATE
Note
Forecast is not a guarantee of future performance.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
8. DASHBOARD
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Dashboard type
Executive Sales Intelligence
Layout
Decision-focused
Sections
• Revenue & Growth
• Orders & AOV
• Regional Performance
• Product Performance
• Trend Analysis
• Anomaly Monitor
• Forecast
• Action Center
Dashboard design
CUSTOMIZED TO DATA + BUSINESS OBJECTIVE
Generic dashboard template
NOT USED
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
9. POWER BI
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✓ Star-schema recommendation
✓ Relationships documented
✓ KPI definitions created
✓ DAX measures generated
✓ Page architecture created
✓ Filter strategy created
Native PBIX
NOT GENERATED
Reason
Power BI execution environment unavailable.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
10. TABLEAU
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✓ Dimensions identified
✓ Measures identified
✓ Calculated fields documented
✓ Dashboard structure created
✓ Filter strategy created
Native Tableau workbook
NOT GENERATED
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
11. EXECUTIVE DECISIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- Investigate West-region decline.
- Review premium-category inventory.
- Monitor high-value revenue anomalies.
- Investigate missing regional customer data.
- Continue monitoring AOV growth.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
12. FILES CREATED
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✓ cleaned_sales.xlsx
✓ analytics_dashboard.xlsx
✓ data_quality_report.md
✓ data_dictionary.md
✓ sales_analysis.sql
✓ analysis.py
✓ dashboard.html
✓ powerbi_model.md
✓ powerbi_measures.dax
✓ tableau_dashboard_spec.md
✓ executive_summary.md
✓ action_plan.md
✓ audit_log.md
FINAL STATUS
ANALYTICS PACKAGE READY
DATA QUALITY
92/100
DASHBOARD
VALIDATED
WARNINGS
3
CRITICAL BLOCKERS
0
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
AI Data Intelligence Command Center™ is an end-to-end analytics workflow that turns messy business data into a complete, customizable analytics package from a single command.
Instead of manually moving between spreadsheets, SQL, Python/R, dashboard tools, and reporting workflows, the skill coordinates the full analytics process:
Collect → Clean → Validate → Model → Analyze → Visualize → Dashboard → Explain → Monitor
It can work with Excel, CSV, JSON, database exports, and other supported business datasets to:
Profile and clean data Detect missing values, duplicates, inconsistencies, anomalies, and schema changes Create a data-quality report and audit trail Build reusable data models and KPI definitions Generate and validate SQL analysis Use Python or R for deeper statistical analysis when appropriate Analyze trends, growth, seasonality, segmentation, funnels, retention, and anomalies Produce forecasts when sufficient historical data exists Create customizable Excel analytics workbooks Generate interactive dashboard-ready outputs Create Power BI-ready data models, DAX measures, and dashboard specifications Create Tableau-ready calculations, data structures, and dashboard specifications Design dashboard layouts using data, audience, and business goals rather than a fixed template Generate executive summaries, findings, and action plans Maintain data lineage showing where important metrics came from Detect data changes and identify when dashboards need to be recalculated Block or flag dashboard updates when critical data-quality problems are detected Preserve the last validated result when a new dataset fails validation One-command workflow
A buyer can provide a dataset and say
“Run the complete analytics workflow and create a decision-ready dashboard.”
The skill determines the appropriate workflow, performs the available analysis, creates the requested outputs, identifies problems, and reports exactly what was verified versus what remains uncertain.
Designed for recurring analytics
When the underlying data changes, the workflow can re-run validation, calculations, insights, and dashboard outputs instead of requiring the dashboard to be manually rebuilt.
Security
The workflow is designed around security-first and least-privilege principles, including minimal permissions, read-only operation by default where possible, no unnecessary network access, protection of credentials, audit logging, and explicit approval for destructive operations.
No software can honestly guarantee absolute security. Security also depends on the user's infrastructure, credentials, connected services, deployment environment, and access configuration.
Important limitation
Native Power BI .pbix, Tableau workbook, or Canva project creation should only be claimed when the required application or integration is actually available in the execution environment. Otherwise, the skill produces Power BI-ready, Tableau-ready, and Canva-ready assets/specifications.
This is not simply a chatbot that describes charts. It is designed as a complete analytics orchestration workflow that produces tangible, customizable outputs and clearly identifies errors, missing evidence, and data-quality risks.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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