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dr-intelligence

Gere pastas de trabalho de inteligência FP&A abrangentes com insights, recomendações e formatação profissional do Excel detectados automaticamente. A habilidade de análise financeira mais poderosa.

556estrelas
Atualizado há 2 meses

Ver no GitHub ↗ Licença: MIT

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Ler descrição completa

FP&A Intelligence Workbook

Generate comprehensive FP&A intelligence workbooks with auto-detected insights, recommendations, and professional Excel formatting.

This is the most powerful financial analysis skill - it answers real business questions, not just data dumps.

What Makes This Different

| Traditional Report | Intelligence Workbook | |-------------------|----------------------| | Shows data | Answers questions | | Lists numbers | Explains "why" | | Static tables | Highlights anomalies | | Manual analysis | Insights auto-surfaced | | Data dump | Recommendations included |

Arguments

| Argument | Description | Default | |----------|-------------|---------| | --year <YYYY> | REQUIRED Calendar year | -- | | --output <file> | Output file path | tmp/FPA_Intelligence_Workbook_YYYY_TIMESTAMP.xlsx |

Workflow

Step 1: Verify Connection

If any Datarails tool call fails with an authentication or connection error, tell the user:

The Datarails connector isn't connected. Click the "+" button next to the prompt, select Connectors, find Datarails, and click Connect.

Then STOP — do not retry until the user has reconnected.

Step 2: Generate Workbook via MCP Tool

Call the generate_intelligence_workbook MCP tool with the parsed arguments:

Use: generate_intelligence_workbook
Arguments:
  year: <parsed year, REQUIRED>
  output_path: <parsed output, or omit for default>

The tool handles:

  • Loading the client profile for the environment
  • Fetching P&L data via aggregation (~5s per query)
  • Fetching KPI, vendor, and cost center data
  • Auto-substituting failed aggregation fields using profile alternatives
  • Calculating insights and recommendations
  • Generating 10-sheet Excel workbook with professional formatting

Step 3: Report Results

Present the generation summary to the user:

  • Output file path
  • Year analyzed
  • Any errors or warnings

10 Sheets Generated

  1. Insights Dashboard - Top 5 findings with severity, key metrics with trends, recommendations
  2. Expense Deep Dive - Top 20 expense accounts with % of total, MoM change
  3. Variance Waterfall - What changed vs prior period and why
  4. Trend Analysis - 12-month trends with growth rates
  5. Anomaly Report - Auto-detected outliers with severity scores
  6. Vendor Analysis - Top 20 vendors, concentration risk flags
  7. SaaS Metrics - ARR waterfall, unit economics, efficiency ratios
  8. Sales Performance - Rep leaderboard, cohort analysis
  9. Cost Center P&L - Department-level detail
  10. Raw Data - Pivot-ready dataset for your own analysis

Auto-Generated Insights

The workbook automatically detects and surfaces:

| Insight Type | Detection Rule | Severity | |--------------|----------------|----------| | OpEx exceeds Revenue | OpEx/Revenue > 1.0 | CRITICAL | | High expense growth | MoM change > 20% | WARNING | | Vendor concentration | Single vendor > 10% of spend | INFO | | Negative margins | Gross profit < 0 | CRITICAL | | Unusual variance | > 3 std deviations | CRITICAL |

Processing Time

  • With aggregation (typical): ~30 seconds
  • With pagination fallback: ~10 minutes for 50K+ rows

Why This Matters

This workbook answers the Top 10 Business Questions:

  1. Where is the money going? - Top 20 expense drivers
  2. What changed vs last month? - MoM variance waterfall
  3. Which cost centers are over budget? - Variance by department
  4. Are we efficient? - OpEx as % of Revenue, Gross Margin
  5. What's unusual? - Auto-detected anomalies
  6. Who are our biggest vendors? - Top 10 vendor spend
  7. How are sales reps performing? - Win rates, ARR by rep
  8. What's our burn situation? - Runway, burn multiple
  9. What should we investigate? - Exception report
  10. What actions to take? - Automated recommendations

Troubleshooting

"profile_not_found" error

Run /dr-learn first to create a profile.

"missing_dependency" error

The MCP server is hosted remotely — this error should not occur. If it does, contact support.

Takes too long

  • With aggregation: should complete in ~30 seconds
  • Run /dr-test to check which fields support aggregation

Missing data in sheets

  • Check if profile has correct field mappings
  • Run /dr-learn to refresh profile

Related Skills

  • /dr-extract - Basic data extraction (simpler, faster)
  • /dr-insights - Executive PowerPoint + Excel combo
  • /dr-anomalies-report - Focused on data quality issues
  • /dr-reconcile - P&L vs KPI validation
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