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Calculate monthly COGS, cost percentages, and manager bonuses (COGS + Top Line) using NET SALES for accuracy and detailed inventory data for restaurant locations.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

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 Γ· 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):

  • βœ… Actual revenue after discounts, comps, voids, returns
  • βœ… True picture of restaurant performance
  • βœ… Accurate bonus calculations
  • βœ… 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 β†’ Inventory costs + COGS details
  • Cantina_Gross_Sales_09_10_25.pdf β†’ NET sales data

Why Both Are Essential:

  • πŸ” 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
  • βœ… Combined = Real inventory costs Γ· actual net revenue = accurate cost percentages

Key Benefits:

  • βœ… Uses NET SALES (actual revenue after discounts/comps/voids)
  • βœ… Uses ACTUAL COGS (beginning inventory + purchases - ending inventory)
  • βœ… More accurate bonus calculations (prevents $40,000+ revenue overstatement)
  • βœ… Auto-extracts location and date from both files
  • βœ… 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 Γ· Category Sales = COGS %

Example:

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

From Usage Report to Bonus Categories

Food bucket:

  • Category Type = "Food"
  • COGS % = Food Usage Γ· Food Sales

Liquor/NA Bev bucket:

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

Beer/Wine bucket:

  • Category Type = "Beer" + "Wine"
  • Combined COGS % = (Beer Usage + Wine Usage) Γ· (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)
    • Reimbursement (amount)
  2. 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:

πŸ“Š [LOCATION] P&L ANALYSIS β€” [MONTH YEAR]

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

━━━ COST PERFORMANCE ━━━

Food COGS: XX.X% (Target: XX%)
β”œβ”€ Usage: $XX,XXX Γ· Sales: $XX,XXX
β”œβ”€ Variance: Β±X.X%
β”œβ”€ $ Impact: $X,XXX
└─ Bonus: $X,XXX βœ“/βœ—

Liquor COGS: XX.X% (Target: XX%)
β”œβ”€ Raw Usage: $XX,XXX
β”œβ”€ Reimbursement: -$X,XXX [if applicable]
β”œβ”€ Adjusted Usage: $XX,XXX
β”œβ”€ COGS %: $XX,XXX Γ· $XX,XXX = XX.X%
β”œβ”€ Variance: Β±X.X%
β”œβ”€ $ Impact: $X,XXX
└─ Bonus: $X,XXX βœ“/βœ—

Beer COGS: XX.X% (Target: XX%)
β”œβ”€ Usage: $XX,XXX Γ· Sales: $XX,XXX
β”œβ”€ Variance: Β±X.X%
β”œβ”€ $ Impact: $X,XXX
└─ Bonus: $X,XXX βœ“/βœ—

Wine COGS: XX.X% (Target: XX%)
β”œβ”€ Usage: $XX,XXX Γ· Sales: $XX,XXX
β”œβ”€ Variance: Β±X.X%
β”œβ”€ $ Impact: $X,XXX
└─ Bonus: $X,XXX βœ“/βœ—

N/A Bev COGS: XX.X%
β”œβ”€ Usage: $XX,XXX Γ· Sales: $XX,XXX
└─ Note: High % typical (ice/mixers)

━━━ BONUS CATEGORY TOTALS ━━━

Liquor/NA Bev Combined: XX.X% (Target: XX%)
β”œβ”€ Combined Sales: $XXX,XXX (Liquor + NA Bev)
β”œβ”€ Combined Usage: $XX,XXX (adjusted for reimbursements)
β”œβ”€ Variance: Β±X.X%
β”œβ”€ $ Impact: $X,XXX
└─ Bonus: $X,XXX βœ“/βœ—

━━━ BONUS SUMMARY ━━━
COGS Bonuses: $XX,XXX
Top Line Bonus: $X,XXX (XX% tier)
β”œβ”€ 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 targetβ€”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 tighteningβ€”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 blockedβ€”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] practicesβ€”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%: βœ… "Hit the $1,800 tier (12.5-13.49%). Just 0.6% away from the $8,400 tierβ€”that's about $2,000 in savings needed."

Example for OAK Food at 31%: βœ… "Missed all bonus tiersβ€”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 β†’ Process standalone
  • If only foodUsageReport.csv β†’ 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 βœ“, 🎯, 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 Γ· 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]

πŸ“Š CANTINA P&L ANALYSIS β€” SEP-OCT 2025 (2 MONTHS)

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

━━━ COST PERFORMANCE ━━━

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

Liquor COGS: 11.4% (Target: 13%) βœ… β”œβ”€ Raw Usage: $121,461.88 β”œβ”€ E11even Reimbursement: -$14,832.00 β”œβ”€ Adjusted Usage: $106,629.88 β”œβ”€ COGS %: $106,629.88 Γ· $932,449.82 = 11.4% β”œβ”€ Variance: -1.6% β”œβ”€ $ Impact: $14,919 under target └─ Bonus: $X,XXX (hit tier)

Beer COGS: 19.9% (Target: 25%) βœ… β”œβ”€ Usage: $42,078.63 Γ· Sales: $211,900.00 β”œβ”€ Variance: -5.1% β”œβ”€ $ Impact: $10,807 under target └─ Bonus: $X,XXX (hit tier)

Wine COGS: 26.2% (Target: 25%) ⚠️ β”œβ”€ Usage: $1,339.96 Γ· Sales: $5,112.00 β”œβ”€ Variance: +1.2% β”œβ”€ $ Impact: $61 over target

N/A Bev COGS: 79.5% β”œβ”€ Usage: $7,112.59 Γ· Sales: $8,945.00 └─ Note: High % typical (ice/mixers)

━━━ BONUS CATEGORY TOTALS ━━━

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

Beer/Wine Combined: 20.2% (Target: 25%) βœ… β”œβ”€ Combined Sales: $217,012.00 (Beer + Wine) β”œβ”€ Combined Usage: $43,418.59 β”œβ”€ Variance: -4.8% β”œβ”€ $ 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 targetβ€”largest issue ($7,288 waste)
  • ⚠️ Liquor just 1% over but $6,129 impact
  • βœ“ Beer/Wine crushing itβ€”3.2% under target
  • πŸ”΄ Top Line blocked (need 2 of 3 COGS targets)

November Action Plan:

  1. πŸ”₯ Food cost emergencyβ€”review portions, waste, comps
  2. 🎯 Liquor controlβ€”check pours, verify E11even credit
  3. βœ… Replicate Beer/Wine practices across categories
  4. πŸ“ˆ 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 β€” ALL LOCATIONS

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

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

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

Action Items:

  • OAK: Focus on food costβ€”get under 30.5% to unlock bonuses
  • WB: Push sales $8K to hit next Top Line tier
  • Cantina: Maintain current practicesβ€”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:

  • βœ“ Know exact bonus amounts in <2 minutes
  • βœ“ Understand which categories need attention
  • βœ“ Have clear action items for next month
  • βœ“ 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.


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

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