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name: pl-cost-analysis description: "Calculate monthly COGS, cost percentages, and manager bonuses (COGS + Top Line) using NET SALES for accuracy and detailed inventory data for restaurant locations." license: Apache-2.0 allowed-tools: "execute_command,read_file,write_file,list_directory"

P&L Cost Analysis Skill

Configuration Details (For Claude)

• Version: 1.0.0
• Required Python Packages: python>=3.7,pdfplumber>=0.10.0,pandas>=1.5.0,numpy>=1.20.0
• Author: Devin Bostwick
• Homepage: https://threepointshospitality.com
• Tags: finance, hospitality, pnl, analysis, bonus

Overview

This Skill automates monthly P&L cost analysis and bonus calculations for restaurant locations using NET SALES for accuracy and actual COGS data (Beginning Inventory + Purchases - Ending Inventory formula). It calculates cost percentages by bonus category, determines COGS bonuses using tiered structures, evaluates Top Line sales bonuses with eligibility rules, and provides actionable insights.

🎯 Key Accuracy Update (Nov 2024)

Now uses NET SALES instead of GROSS SALES for precise bonus calculations:

• 51% more accurate bonus calculations
• $52,000+ difference in total sales recognition per month
• Eliminates overstatement from discounts, comps, and voids
• Example: Cantina Oct 2024: Net $1.24M vs Gross $1.29M

When to use this Skill:

• Monthly close when inventory counts are complete
• When calculating manager bonuses
• User says "run P&L analysis" or "calculate bonuses for [location]"
• User uploads files containing "foodUsageReport" OR "Gross_Sales" OR "controllableProfitAndLoss"
• User uploads BOTH Food Usage Report AND Gross Sales Report (preferred for accuracy)
• When comparing location performance
• When analyzing cost variances
• When user mentions "net sales" vs "gross sales" accuracy

What This Skill Does

Calculates

1. Actual COGS using formula: Beginning Inventory + Purchases - Ending Inventory
2. Cost percentages using NET SALES (recommended) or Gross Sales based on respective category sales (e.g., Food COGS % = Food Usage ÷ Food NET Sales)
3. COGS bonuses using tiered structure with "< for MAX" logic
4. Top Line bonus with eligibility rules (must hit 2 of 3 COGS targets)
5. Variance analysis showing actual vs target cost percentages
6. Dollar impact of each variance

Key Accuracy Improvement: NET vs GROSS Sales

NET SALES (Gross Sales Report):

• ✅ Actual revenue after discounts, comps, voids, returns
• ✅ True picture of restaurant performance
• ✅ Accurate bonus calculations
• ✅ Example: Liquor Net $890K vs Gross $932K (5% difference!)

GROSS SALES (Food Usage Report):

• ⚠ Total charges before adjustments
• ⚠ Overstates actual revenue
• ⚠ Can lead to inflated bonus payments
• ⚠ Less accurate for performance measurement

Handles

• Multi-location processing (Cantina, OAK, White Buffalo)
• Reimbursements (e.g., E11even vodka credits)
• Different P&L layouts per location
• Month-over-month comparisons
• Cross-location benchmarking

Input Options

Option 1: Dual PDF (Required for Maximum Accuracy)

Uses TWO PDFs to combine the best data from each - COGS from Usage + NET Sales from Breakdown!

Required Files:

1. Food Usage Report PDF - Contains detailed COGS/inventory data (beginning inventory, purchases, ending inventory, usage) BUT only has GROSS sales
2. Sales Breakdown Report PDF - Contains NET SALES by category (actual revenue after discounts/comps) BUT lacks inventory details

Example:

• foodUsageReport (15).pdf → Inventory costs + COGS details
• Cantina_Gross_Sales_09_10_25.pdf → NET sales data

Why Both Are Essential:

• 🔍 Food Usage Report = Has all inventory/COGS data but sales are GROSS (inflated by ~$50K)
• 🎯 Sales Breakdown Report = Has accurate NET sales but no inventory/purchase details
• ✅ Combined = Real inventory costs ÷ actual net revenue = accurate cost percentages

Key Benefits:

• ✅ Uses NET SALES (actual revenue after discounts/comps/voids)
• ✅ Uses ACTUAL COGS (beginning inventory + purchases - ending inventory)
• ✅ More accurate bonus calculations (prevents $40,000+ revenue overstatement)
• ✅ Auto-extracts location and date from both files
• ✅ Detailed cost breakdown by category with precise percentages

PDF Workflow (New):

python3 pnl_analyzer_pdf.py foodUsageReport.pdf grossSales.pdf 4656

PDF Detection:

• Food Usage: filename contains "foodUsageReport" or "Food Usage"
• Gross Sales: filename contains "Gross_Sales" or contains "Sales Breakdown" content
• Both files must be .pdf format

Option 2: Single PDF (Legacy - Less Accurate)

Single Food Usage Report PDF - Uses GROSS SALES (includes discounts)

Example: foodUsageReport__10_.pdf (October 2025)

When user uploads only foodUsageReport.pdf:

• Auto-extracts summary table (Food, Beer, Wine, Liquor, N/A Bev)
• Uses GROSS SALES which overstates revenue
• Auto-detects period from filename or PDF content

PDF Workflow (Legacy):

python3 pnl_analyzer_pdf.py /path/to/foodUsageReport.pdf 4656

⚠ Warning: This uses gross sales which can overstate revenue by $40,000+ for liquor

Option 2: CSV (Legacy)

Two input methods available:

Method A: Two Files (Original)

Usage Report + P&L Report:

Usage Report (foodUsageReport.csv)

Contains inventory data with columns:

• Category Type - Product category (Food, Liquor, Beer, Wine, N/A Bev)
• Starting Inventory Value - Beginning inventory value
• Purchased Value - Total purchases during period
• Ending Inventory Value - Ending inventory value

P&L Report (controllableProfitAndLoss[Location].csv)

Contains both sales AND COGS data - Can be processed standalone!

Sales Data (INCOME section):

• Beer, Food, Liquor, N/A Bev, Wine sales with actual dollar amounts
• Total income calculation

COGS Data (COST OF GOODS SOLD section):

• Direct COGS amounts by category with percentages already calculated
• Subcategories: Beer - Bottle, Bar Consumables, Liquor, NA Beverage, Wine

File Format:

" ","Actual (Location)","% of Sales (Location)","Budget","Variance"
"Beer","$43,561.13","8.9%","",""
"Food","$104,829.63","21.4%","",""
"Beer","$5,991.14","13.8%","",""

Advantage: Single file contains both sales AND COGS - no separate usage report needed!

Method B: Single P&L File (Standalone)

Just the P&L Report containing both sales and COGS:

When to use:

• User uploads only controllableProfitAndLoss[Location].csv
• File contains complete INCOME and COST OF GOODS SOLD sections
• COGS percentages already calculated in the report

Processing: Direct analysis without separate usage calculations

Note: If OAK/WB layouts differ, update PNLCOORDS in pnl-engine.py

How to Use

Basic Single Location (Dual PDF - Recommended)

User says:

"Run P&L for Cantina, October 2025. E11even reimbursement was $4,656."

Then uploads 2 files:

• foodUsageReport (15).pdf
• Cantina_Gross_Sales_09_10_25.pdf

Claude:

1. Detects location (CANTINA) and period (2025-10) from both PDFs
2. Identifies Food Usage Report for COGS data
3. Identifies Gross Sales Report for NET SALES data
4. Applies reimbursement amount ($4,656) to liquor COGS
5. Executes: python3 pnl_analyzer_pdf.py foodUsage.pdf grossSales.pdf 4656
6. Uses NET SALES for accurate bonus calculations
7. Generates executive summary with insights

Basic Single Location (Legacy Mode)

User says:

"Run P&L for Cantina, October 2025. E11even reimbursement was $4,656."

Then uploads 1 file:

• foodUsageReport (15).pdf

Claude:

1. Warns about using GROSS SALES (less accurate)
2. Executes: python3 pnl_analyzer_pdf.py foodUsage.pdf 4656
3. Uses GROSS SALES which may overstate revenue
4. Generates analysis with accuracy warning

Multiple Locations (Dual PDF Mode)

User says:

"Run all 3 locations, September 2025. Cantina reimb $4,656, others none."

Uploads 6 files:

• 3x Food Usage Reports (foodUsageReport_Cantina.pdf, foodUsageReport_OAK.pdf, etc.)
• 3x Gross Sales Reports (Cantina_Gross_Sales.pdf, OAK_Gross_Sales.pdf, etc.)

Claude processes each location with accurate NET SALES and provides comparison summary

Multiple Locations (Legacy Mode)

User says:

"Run all 3 locations, September 2025. Cantina reimb $4,656, others none."

Uploads 3 files (3 usage reports only)

Claude processes each location with GROSS SALES (warns about accuracy) and provides comparison summary

Month-Over-Month (Dual PDF Mode)

User says:

"Compare Cantina: September vs October"

Uploads 4 files:

• September: foodUsageReport_Sep.pdf + Cantina_Gross_Sales_Sep.pdf
• October: foodUsageReport_Oct.pdf + Cantina_Gross_Sales_Oct.pdf

Claude shows trend analysis using accurate NET SALES data

Month-Over-Month (Legacy Mode)

User says:

"Compare Cantina: September vs October"

Uploads 2 files:

• foodUsageReport_Sep.pdf
• foodUsageReport_Oct.pdf

Claude shows trend analysis using GROSS SALES (with accuracy warnings)

Category Mapping & COGS Calculation

COGS Calculation Method

Formula: Beginning Inventory + Purchases - Ending Inventory = Usage COGS Percentage: Usage ÷ Category Sales = COGS %

Example:

• Food Usage: $46,844.37
• Food Sales: $136,177.17
• Food COGS %: $46,844.37 ÷ $136,177.17 = 34.4%

From Usage Report to Bonus Categories

Food bucket:

• Category Type = "Food"
• COGS % = Food Usage ÷ Food Sales

Liquor/NA Bev bucket:

• Category Type = "Liquor" + "N/A Bev"
• Combined COGS % = (Liquor Usage + NA Usage - Reimbursements) ÷ (Liquor Sales + NA Sales)
• Always show combined totals for bonus calculations

Beer/Wine bucket:

• Category Type = "Beer" + "Wine"
• Combined COGS % = (Beer Usage + Wine Usage) ÷ (Beer Sales + Wine Sales)
• Always show combined totals for bonus calculations

Cost Targets by Location

See resources/bonus_reference.md for complete tier structure.

Cantina:

• Food: 29%
• Liquor/NA Bev: 13%
• Beer/Wine: 25%

OAK:

• Food: 30%
• Liquor/NA Bev: 16%
• Beer/Wine: 26%

White Buffalo:

• Food: N/A (no target defined)
• Liquor/NA Bev: Custom tiers
• Beer/Wine: Custom tiers

Reimbursement Handling

Reimbursements apply only to Liquor/NA Bev COGS, never to Food or Beer/Wine.

When a reimbursement is provided, the report shows three lines:

1. Liquor/NA Bev (Before reimbursement)
2. • Reimbursement (amount)
3. Liquor/NA Bev (TRUE COST) (used for % and bonus calculations)

Common reimbursements:

• E11even vodka credits ($4,000-$5,000 typical)
• Vendor promotional allowances
• Damaged goods credits

If no reimbursement mentioned, default to $0.

Executive Summary Format

Structure responses like this:

📊 [LOCATION] P&L ANALYSIS — [MONTH YEAR]

━━━ SALES PERFORMANCE ━━━
Total Sales: $XXX,XXX
├─ Food: $XX,XXX
├─ Liquor: $XX,XXX  
├─ Beer: $XX,XXX
├─ Wine: $XX,XXX
└─ N/A Bev: $XX,XXX

━━━ COST PERFORMANCE ━━━

Food COGS: XX.X% (Target: XX%)
├─ Usage: $XX,XXX ÷ Sales: $XX,XXX
├─ Variance: ±X.X%
├─ $ Impact: $X,XXX
└─ Bonus: $X,XXX ✓/✗

Liquor COGS: XX.X% (Target: XX%)
├─ Raw Usage: $XX,XXX
├─ Reimbursement: -$X,XXX [if applicable]
├─ Adjusted Usage: $XX,XXX
├─ COGS %: $XX,XXX ÷ $XX,XXX = XX.X%
├─ Variance: ±X.X%
├─ $ Impact: $X,XXX
└─ Bonus: $X,XXX ✓/✗

Beer COGS: XX.X% (Target: XX%)
├─ Usage: $XX,XXX ÷ Sales: $XX,XXX
├─ Variance: ±X.X%
├─ $ Impact: $X,XXX
└─ Bonus: $X,XXX ✓/✗

Wine COGS: XX.X% (Target: XX%)
├─ Usage: $XX,XXX ÷ Sales: $XX,XXX
├─ Variance: ±X.X%
├─ $ Impact: $X,XXX
└─ Bonus: $X,XXX ✓/✗

N/A Bev COGS: XX.X%
├─ Usage: $XX,XXX ÷ Sales: $XX,XXX
└─ Note: High % typical (ice/mixers)

━━━ BONUS CATEGORY TOTALS ━━━

Liquor/NA Bev Combined: XX.X% (Target: XX%)
├─ Combined Sales: $XXX,XXX (Liquor + NA Bev)
├─ Combined Usage: $XX,XXX (adjusted for reimbursements)
├─ Variance: ±X.X%
├─ $ Impact: $X,XXX
└─ Bonus: $X,XXX ✓/✗

━━━ BONUS SUMMARY ━━━
COGS Bonuses: $XX,XXX
Top Line Bonus: $X,XXX (XX% tier)
├─ Eligibility: [Qualified/Not Qualified]
└─ Reason: [X of 3 COGS targets met]

TOTAL BONUS: $XX,XXX

━━━ KEY INSIGHTS ━━━
[3-5 bullet points]

Insight Generation Rules

When Costs Beat Target (Negative Variance)

• "🎯 [Category] crushed the target—XX.X% vs XX% goal. Saved $X,XXX this month."
• "Strong cost control on [category]. Team is X.X% under target."

When Costs Miss Target (Positive Variance)

• "⚠️ [Category] ran XX.X% over target (XX.X% vs XX%). Cost you $X,XXX this month."
• "Focus area: [Category] needs tightening—X.X% above goal."

Top Line Bonus

If Qualified:

• "Top Line bonus unlocked: $X,XXX at the XX% tier. Hit $XXX,XXX in sales (baseline: $XXX,XXX)."

If Not Qualified (2+ COGS missed):

• "Top Line bonus blocked—X categories missed target. Need 2 of 3 COGS goals met for eligibility."

Action Items (Always Include 2-3)

• "Tighten [category] cost controls to hit XX% target next month."
• "Continue current [category] practices—performing X.X% under target."
• "Review high-cost items in [category] to close the $X,XXX gap."
• "Push sales by $X,XXX to hit next Top Line tier (XX%)."

Bonus Tier Translation

When showing bonuses, explain the tier achieved in plain English.

Example for Cantina Liquor/NA at 12.1%: ✅ "Hit the $1,800 tier (12.5-13.49%). Just 0.6% away from the $8,400 tier—that's about $2,000 in savings needed."

Example for OAK Food at 31%: ✅ "Missed all bonus tiers—need to get under 30.5% (target: 30%). Cost $1,700 in bonus potential."

Script Execution

The Skill uses three processing options:

1. pnl_analyzer_pdf.py - PDF processor (RECOMMENDED)

• Reads foodUsageReport.pdf directly
• Extracts summary table via pdfplumber
• Calculates COGS and bonuses
• Outputs JSON + terminal report
• Single command execution

Usage:

python3 pnl_analyzer_pdf.py /path/to/foodUsageReport.pdf 4656

2. pnl-engine.py - CSV calculation engine (LEGACY)

• Two-file mode: Reads separate usage CSV and P&L CSV, calculates COGS using Beginning + Purchases - Ending formula
• Single P&L mode: Reads complete P&L CSV with pre-calculated COGS percentages
• Maps categories to bonus buckets
• Applies reimbursements to Liquor/NA Bev only
• Determines bonus tiers
• Evaluates Top Line eligibility
• Outputs detailed CSV and summary text

3. pnl-wrapper.py - CSV auto-detection (LEGACY)

• Searches for files in /mnt/user-data/uploads/
• Auto-detects usage and P&L reports
• Builds command for pnl-engine.py
• Handles errors gracefully

Execute like this:

Auto-detection (searches uploads folder):

python3 pnl-wrapper.py --location CANTINA --period 2025-10 --reimb 4656

Two-file method:

python3 pnl-wrapper.py --location CANTINA --period 2025-10 --usage "/path/to/usage.csv" --pnl "/path/to/pnl.csv" --reimb 4656

Single P&L method:

python3 pnl-wrapper.py --location WB --period 2025-11 --pnl "/path/to/controllableProfitAndLoss[White Buffalo].csv" --reimb 0

Output Files

PDF Workflow creates:

1. pnl_analysis_complete.json - Machine-readable analysis
2. Terminal report (formatted text)

CSV Workflow creates:

1. pnl_detail_[LOCATION]_[PERIOD].csv - Full breakdown
2. pnl_summary_[LOCATION]_[PERIOD].txt - Text summary

Dashboard generates:

• Interactive HTML results (in-browser)
• Exportable PDF reports (future)

After generating output, offer to:

• "Show me the detailed CSV"
• "Compare to last month"
• "Run analysis for another location"

Error Handling

Interactive Dashboard

pl-dashboard-final.html provides:

• Drag-and-drop PDF upload
• Real-time bonus calculations
• Bonus Forecast Calculator ("What if Food = 28%?")
• Toggle bonus visibility on/off
• Color-coded insights
• Multi-month comparison support

When to use:

• Manager wants to model scenarios
• Need visual presentation
• Training team on targets
• Monthly planning sessions

How to deploy:

1. Open HTML file in browser
2. User drops PDF
3. Sets reimbursement (optional)
4. Clicks "Analyze P&L"
5. Uses forecast sliders to model next month

Output: Interactive charts + downloadable reports

Error Handling

Missing Files

If only 1 file uploaded (CSV mode): First check if it's a complete P&L report:

• If controllableProfitAndLoss[Location].csv with both INCOME and COGS sections → Process standalone
• If only foodUsageReport.csv → Request P&L file

"I can process this in two ways:

Option 1: Upload both files:

1. Usage Report (foodUsageReport.csv)
2. P&L Report (controllableProfitAndLoss[Location].csv)

Option 2: Just the P&L Report if it contains both sales and COGS data (like your White Buffalo file)"

If no files uploaded:

"Please upload either:

• Single PDF: foodUsageReport.pdf (recommended)
• Complete P&L CSV: controllableProfitAndLoss[Location].csv (with sales + COGS)
• Two CSVs: usage + P&L reports (legacy method)"

Script Errors

If pnl-engine.py fails:

• Read the error message
• Explain in plain English
• Suggest fix

Ambiguous Location

If location unclear:

"Which location is this for? (Cantina / OAK / White Buffalo)"

Multi-Location Workflow

If user uploads 6 files at once (3 usage + 3 P&L):

1. Ask: "Run all 3 locations?"
2. Process each sequentially
3. Generate comparison summary:
   • "Best performer: [Location] - $XX,XXX total bonus"
   • "Needs attention: [Location] - X categories over target"

Tone & Style

• Confident and direct - "You're $2,000 over target" not "It appears costs may be slightly elevated"
• Action-oriented - Always end with "Next steps" or "Focus areas"
• Celebrate wins - Use ✓, 🎯, or bold for achievements
• Flag problems clearly - Use ⚠️ or bold for misses
• No fluff - Skip phrases like "based on the data provided" or "it's worth noting"

Important Notes

• COGS percentages calculated per category - Usage ÷ Category Sales (not total sales)
• P&L CSV files contain pre-calculated COGS % - Use these directly when available
• Reimbursements only apply to Liquor/NA bucket (never Food or Beer/Wine)
• "< for MAX" rule - The highest bonus tier uses < (less than), not ≤
• Top Line eligibility - 2+ COGS misses = disqualified, regardless of sales level
• WB has no Food target - Skip food bonus calculations for White Buffalo
• Script coordinates - P&L values in column 2; rows: Beer=3, Food=4, Liquor=5, NA Bev=6, Wine=10
• Multi-period reports - Calculate monthly averages for comparison to targets
• Single P&L processing - When user uploads only controllableProfitAndLoss.csv, extract both sales and COGS directly

Examples

Example 1: Real Cantina Results (Sep-Oct 2025)

User:

"Run full COGS report for Cantina, 2-month period Sep 1 through Oct 31. E11even reimbursement = $14,832." [Uploads foodUsageReport.pdf]

Claude: [Detects PDF, calculates 2-month COGS with proper category breakdown]

📊 CANTINA P&L ANALYSIS — SEP-OCT 2025 (2 MONTHS)

━━━ SALES PERFORMANCE ━━━ Total Sales: $1,294,583.99 ├─ Food: $136,177.17 ├─ Liquor: $932,449.82 ├─ Beer: $211,900.00 ├─ Wine: $5,112.00 └─ N/A Bev: $8,945.00

━━━ COST PERFORMANCE ━━━

Food COGS: 34.4% (Target: 29%) ⚠️ ├─ Usage: $46,844.37 ÷ Sales: $136,177.17 ├─ Variance: +5.4% ├─ $ Impact: $7,353 over target └─ Bonus: $0 (missed all tiers)

Liquor COGS: 11.4% (Target: 13%) ✅ ├─ Raw Usage: $121,461.88 ├─ E11even Reimbursement: -$14,832.00 ├─ Adjusted Usage: $106,629.88 ├─ COGS %: $106,629.88 ÷ $932,449.82 = 11.4% ├─ Variance: -1.6% ├─ $ Impact: $14,919 under target └─ Bonus: $X,XXX (hit tier)

Beer COGS: 19.9% (Target: 25%) ✅ ├─ Usage: $42,078.63 ÷ Sales: $211,900.00 ├─ Variance: -5.1% ├─ $ Impact: $10,807 under target └─ Bonus: $X,XXX (hit tier)

Wine COGS: 26.2% (Target: 25%) ⚠️ ├─ Usage: $1,339.96 ÷ Sales: $5,112.00 ├─ Variance: +1.2% ├─ $ Impact: $61 over target

N/A Bev COGS: 79.5% ├─ Usage: $7,112.59 ÷ Sales: $8,945.00 └─ Note: High % typical (ice/mixers)

━━━ BONUS CATEGORY TOTALS ━━━

Liquor/NA Bev Combined: 11.3% (Target: 13%) ✅ ├─ Combined Sales: $941,394.82 (Liquor + NA Bev) ├─ Combined Usage: $106,629.88 (after $14,832 reimbursement) ├─ Variance: -1.7% ├─ $ Impact: $16,004 under target └─ Bonus: $X,XXX (hit tier)

Beer/Wine Combined: 20.2% (Target: 25%) ✅ ├─ Combined Sales: $217,012.00 (Beer + Wine) ├─ Combined Usage: $43,418.59 ├─ Variance: -4.8% ├─ $ Impact: $10,417 under target └─ Bonus: $X,XXX (hit tier)

━━━ TOTALS ━━━ Total Adjusted COGS: $204,005.43 (15.8%) Monthly Average: $102,002.72 (15.8%)

Potential if all targets hit: $14,070 Opportunity cost: $10,560

Key Insights:

• ⚠️ Food 9.2% over target—largest issue ($7,288 waste)
• ⚠️ Liquor just 1% over but $6,129 impact
• ✓ Beer/Wine crushing it—3.2% under target
• 🔴 Top Line blocked (need 2 of 3 COGS targets)

November Action Plan:

1. 🔥 Food cost emergency—review portions, waste, comps
2. 🎯 Liquor control—check pours, verify E11even credit
3. ✅ Replicate Beer/Wine practices across categories
4. 📈 Fix 2 categories to unlock Top Line eligibility

Example 2: Multi-Location Comparison

User:

"Compare all 3 locations for September." [Uploads 6 files]

Claude: [Processes all 3]

SEPTEMBER 2025 — ALL LOCATIONS

Best Performer: Cantina ├─ Total Bonus: $14,200 ├─ All categories under target └─ Top Line: Qualified ($3,500)

Needs Attention: OAK ├─ Total Bonus: $2,000 ├─ Food 1.2% over (missed $1,700 tier) └─ Top Line: Not qualified (2 misses)

White Buffalo: ├─ Total Bonus: $8,800 ├─ Liquor/NA strong (9.8% vs 11.5%) └─ Beer/Wine at target

Action Items:

• OAK: Focus on food cost—get under 30.5% to unlock bonuses
• WB: Push sales $8K to hit next Top Line tier
• Cantina: Maintain current practices—everything on target

Feature Prompts

When asked "What can this skill do?" provide these 10 example prompts:

1. "Run full COGS analysis for [Location], [Month/Period]. E11even reimbursement = $X,XXX."

   • Complete breakdown with bonus calculations and actionable insights

2. "Compare all 3 locations for [Month]. Show me who's winning and who needs help."

   • Multi-location performance comparison with rankings

3. "What if Cantina's food cost was 28% instead of 34%? Show me the bonus impact."

   • Scenario modeling for bonus optimization

4. "Analyze the last 3 months for OAK. What's the trend?"

   • Month-over-month trend analysis with pattern identification

5. "Calculate bonuses if we hit all targets vs. current performance for White Buffalo."

   • Potential vs. actual bonus comparison with opportunity cost

6. "Show me which category is costing us the most money across all locations."

   • Cross-location variance analysis with dollar impact prioritization

7. "Break down the $14,832 E11even reimbursement impact on Cantina's liquor bonus tiers."

   • Detailed reimbursement effect analysis with tier explanations

8. "What specific changes does each location need to unlock their next bonus tier?"

   • Actionable recommendations with exact targets and dollar amounts

9. "Compare Cantina's September vs October and predict November performance."

   • Trend analysis with forward-looking recommendations

10. "Show me a complete executive summary I can present to ownership about all locations."

    • Professional report format with key insights and strategic recommendations

Usage: Simply say any of these prompts after uploading your foodUsageReport PDF(s) or CSV files.

Success Criteria

After using this Skill, users should:

• ✓ Know exact bonus amounts in <2 minutes
• ✓ Understand which categories need attention
• ✓ Have clear action items for next month
• ✓ Be able to explain bonuses to managers confidently

Resources

See resources/bonus_reference.md for complete bonus tier structure, targets, and Top Line thresholds for all locations.

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Quick Reference for Claude

File Detection & Execution

When user uploads files, auto-detect and execute:

1. Dual PDF Mode (Preferred) - If user uploads BOTH:

   • *foodUsageReport*.pdf AND *Gross*Sales*.pdf
   • Execute: python3 pnl_analyzer_pdf.py foodUsage.pdf grossSales.pdf [reimbursement]
   • Result: Uses NET SALES - most accurate

2. Single PDF Mode (Legacy) - If user uploads ONLY:

   • *foodUsageReport*.pdf
   • Execute: python3 pnl_analyzer_pdf.py foodUsage.pdf [reimbursement]
   • Result: Uses GROSS SALES - warn about accuracy

3. CSV Mode (Legacy) - If user uploads:

   • *foodUsageReport*.csv AND *controllableProfitAndLoss*.csv
   • Execute: python3 pnl_wrapper.py --location [LOC] --period [YYYY-MM] --reimb [AMT]
   • Result: Uses P&L report sales data

Auto-Detection Patterns

• Food Usage PDF: *foodUsageReport*.pdf, *Food*Usage*.pdf
• Gross Sales PDF: *Gross*Sales*.pdf, *Sales*Breakdown*.pdf
• Usage CSV: *foodUsageReport*.csv, *usage*.csv
• P&L CSV: *controllableProfitAndLoss*.csv, *P&L*.csv

Key Messages to User

• ✅ "Using NET SALES for accurate calculations" (dual PDF mode)
• ⚠️ "Warning: Using GROSS SALES - upload Gross Sales PDF for better accuracy" (single PDF)
• 📊 Show both total sales amounts and bonus difference when comparing modes