| 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.
π― 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
- Actual COGS using formula: Beginning Inventory + Purchases - Ending Inventory
- Cost percentages using NET SALES (recommended) or Gross Sales based on respective category sales (e.g., Food COGS % = Food Usage Γ· Food NET Sales)
- COGS bonuses using tiered structure with "< for MAX" logic
- Top Line bonus with eligibility rules (must hit 2 of 3 COGS targets)
- Variance analysis showing actual vs target cost percentages
- Dollar impact of each variance
Key Accuracy Improvement: NET vs GROSS Sales
NET SALES (Gross Sales Report):
- β Actual revenue after discounts, comps, voids, returns
- β True picture of restaurant performance
- β Accurate bonus calculations
- β Example: Liquor Net $890K vs Gross $932K (5% difference!)
GROSS SALES (Food Usage Report):
- β Total charges before adjustments
- β Overstates actual revenue
- β Can lead to inflated bonus payments
- β 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:
- Food Usage Report PDF - Contains detailed COGS/inventory data (beginning inventory, purchases, ending inventory, usage) BUT only has GROSS sales
- Sales Breakdown Report PDF - Contains NET SALES by category (actual revenue after discounts/comps) BUT lacks inventory details
Example:
foodUsageReport (15).pdfβ Inventory costs + COGS detailsCantina_Gross_Sales_09_10_25.pdfβ NET sales data
Why Both Are Essential:
- π Food Usage Report = Has all inventory/COGS data but sales are GROSS (inflated by ~$50K)
- π― Sales Breakdown Report = Has accurate NET sales but no inventory/purchase details
- β Combined = Real inventory costs Γ· actual net revenue = accurate cost percentages
Key Benefits:
- β Uses NET SALES (actual revenue after discounts/comps/voids)
- β Uses ACTUAL COGS (beginning inventory + purchases - ending inventory)
- β More accurate bonus calculations (prevents $40,000+ revenue overstatement)
- β Auto-extracts location and date from both files
- β 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
.pdfformat
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
β 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).pdfCantina_Gross_Sales_09_10_25.pdf
Claude:
- Detects location (CANTINA) and period (2025-10) from both PDFs
- Identifies Food Usage Report for COGS data
- Identifies Gross Sales Report for NET SALES data
- Applies reimbursement amount ($4,656) to liquor COGS
- Executes:
python3 pnl_analyzer_pdf.py foodUsage.pdf grossSales.pdf 4656 - Uses NET SALES for accurate bonus calculations
- 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:
- Warns about using GROSS SALES (less accurate)
- Executes:
python3 pnl_analyzer_pdf.py foodUsage.pdf 4656 - Uses GROSS SALES which may overstate revenue
- 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.pdffoodUsageReport_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:
- Liquor/NA Bev (Before reimbursement)
- Reimbursement (amount)
- 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:
π [LOCATION] P&L ANALYSIS β [MONTH YEAR]
βββ SALES PERFORMANCE βββ
Total Sales: $XXX,XXX
ββ Food: $XX,XXX
ββ Liquor: $XX,XXX
ββ Beer: $XX,XXX
ββ Wine: $XX,XXX
ββ N/A Bev: $XX,XXX
βββ COST PERFORMANCE βββ
Food COGS: XX.X% (Target: XX%)
ββ Usage: $XX,XXX Γ· Sales: $XX,XXX
ββ Variance: Β±X.X%
ββ $ Impact: $X,XXX
ββ Bonus: $X,XXX β/β
Liquor COGS: XX.X% (Target: XX%)
ββ Raw Usage: $XX,XXX
ββ Reimbursement: -$X,XXX [if applicable]
ββ Adjusted Usage: $XX,XXX
ββ COGS %: $XX,XXX Γ· $XX,XXX = XX.X%
ββ Variance: Β±X.X%
ββ $ Impact: $X,XXX
ββ Bonus: $X,XXX β/β
Beer COGS: XX.X% (Target: XX%)
ββ Usage: $XX,XXX Γ· Sales: $XX,XXX
ββ Variance: Β±X.X%
ββ $ Impact: $X,XXX
ββ Bonus: $X,XXX β/β
Wine COGS: XX.X% (Target: XX%)
ββ Usage: $XX,XXX Γ· Sales: $XX,XXX
ββ Variance: Β±X.X%
ββ $ Impact: $X,XXX
ββ Bonus: $X,XXX β/β
N/A Bev COGS: XX.X%
ββ Usage: $XX,XXX Γ· Sales: $XX,XXX
ββ Note: High % typical (ice/mixers)
βββ BONUS CATEGORY TOTALS βββ
Liquor/NA Bev Combined: XX.X% (Target: XX%)
ββ Combined Sales: $XXX,XXX (Liquor + NA Bev)
ββ Combined Usage: $XX,XXX (adjusted for reimbursements)
ββ Variance: Β±X.X%
ββ $ Impact: $X,XXX
ββ Bonus: $X,XXX β/β
βββ BONUS SUMMARY βββ
COGS Bonuses: $XX,XXX
Top Line Bonus: $X,XXX (XX% tier)
ββ Eligibility: [Qualified/Not Qualified]
ββ Reason: [X of 3 COGS targets met]
TOTAL BONUS: $XX,XXX
βββ KEY INSIGHTS βββ
[3-5 bullet points]
Insight Generation Rules
When Costs Beat Target (Negative Variance)
- "π― [Category] crushed the targetβXX.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)
- "β οΈ [Category] ran XX.X% over target (XX.X% vs XX%). Cost you $X,XXX this month."
- "Focus area: [Category] needs tighteningβX.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 blockedβX 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] practicesβperforming 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%: β "Hit the $1,800 tier (12.5-13.49%). Just 0.6% away from the $8,400 tierβthat's about $2,000 in savings needed."
Example for OAK Food at 31%: β "Missed all bonus tiersβneed 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:
pnl_analysis_complete.json- Machine-readable analysis- Terminal report (formatted text)
CSV Workflow creates:
pnl_detail_[LOCATION]_[PERIOD].csv- Full breakdownpnl_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:
- Open HTML file in browser
- User drops PDF
- Sets reimbursement (optional)
- Clicks "Analyze P&L"
- 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].csvwith both INCOME and COGS sections β Process standalone - If only
foodUsageReport.csvβ Request P&L file
"I can process this in two ways:
Option 1: Upload both files:
- Usage Report (foodUsageReport.csv)
- 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):
- Ask: "Run all 3 locations?"
- Process each sequentially
- 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 β, π―, or bold for achievements
- Flag problems clearly - Use β οΈ 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 β€
- 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]
π CANTINA P&L ANALYSIS β SEP-OCT 2025 (2 MONTHS)
βββ SALES PERFORMANCE βββ Total Sales: $1,294,583.99 ββ Food: $136,177.17 ββ Liquor: $932,449.82 ββ Beer: $211,900.00 ββ Wine: $5,112.00 ββ N/A Bev: $8,945.00
βββ COST PERFORMANCE βββ
Food COGS: 34.4% (Target: 29%) β οΈ ββ Usage: $46,844.37 Γ· Sales: $136,177.17 ββ Variance: +5.4% ββ $ Impact: $7,353 over target ββ Bonus: $0 (missed all tiers)
Liquor COGS: 11.4% (Target: 13%) β ββ Raw Usage: $121,461.88 ββ E11even Reimbursement: -$14,832.00 ββ Adjusted Usage: $106,629.88 ββ COGS %: $106,629.88 Γ· $932,449.82 = 11.4% ββ Variance: -1.6% ββ $ Impact: $14,919 under target ββ Bonus: $X,XXX (hit tier)
Beer COGS: 19.9% (Target: 25%) β ββ Usage: $42,078.63 Γ· Sales: $211,900.00 ββ Variance: -5.1% ββ $ Impact: $10,807 under target ββ Bonus: $X,XXX (hit tier)
Wine COGS: 26.2% (Target: 25%) β οΈ ββ Usage: $1,339.96 Γ· Sales: $5,112.00 ββ Variance: +1.2% ββ $ Impact: $61 over target
N/A Bev COGS: 79.5% ββ Usage: $7,112.59 Γ· Sales: $8,945.00 ββ Note: High % typical (ice/mixers)
βββ BONUS CATEGORY TOTALS βββ
Liquor/NA Bev Combined: 11.3% (Target: 13%) β ββ Combined Sales: $941,394.82 (Liquor + NA Bev) ββ Combined Usage: $106,629.88 (after $14,832 reimbursement) ββ Variance: -1.7% ββ $ Impact: $16,004 under target ββ Bonus: $X,XXX (hit tier)
Beer/Wine Combined: 20.2% (Target: 25%) β ββ Combined Sales: $217,012.00 (Beer + Wine) ββ Combined Usage: $43,418.59 ββ Variance: -4.8% ββ $ Impact: $10,417 under target ββ Bonus: $X,XXX (hit tier)
βββ TOTALS βββ 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:
- β οΈ Food 9.2% over targetβlargest issue ($7,288 waste)
- β οΈ Liquor just 1% over but $6,129 impact
- β Beer/Wine crushing itβ3.2% under target
- π΄ Top Line blocked (need 2 of 3 COGS targets)
November Action Plan:
- π₯ Food cost emergencyβreview portions, waste, comps
- π― Liquor controlβcheck pours, verify E11even credit
- β Replicate Beer/Wine practices across categories
- π 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 ββ Total Bonus: $14,200 ββ All categories under target ββ Top Line: Qualified ($3,500)
Needs Attention: OAK ββ Total Bonus: $2,000 ββ Food 1.2% over (missed $1,700 tier) ββ Top Line: Not qualified (2 misses)
White Buffalo: ββ Total Bonus: $8,800 ββ Liquor/NA strong (9.8% vs 11.5%) ββ Beer/Wine at target
Action Items:
- OAK: Focus on food costβget under 30.5% to unlock bonuses
- WB: Push sales $8K to hit next Top Line tier
- Cantina: Maintain current practicesβeverything on target
Feature Prompts
When asked "What can this skill do?" provide these 10 example prompts:
"Run full COGS analysis for [Location], [Month/Period]. E11even reimbursement = $X,XXX."
- Complete breakdown with bonus calculations and actionable insights
"Compare all 3 locations for [Month]. Show me who's winning and who needs help."
- Multi-location performance comparison with rankings
"What if Cantina's food cost was 28% instead of 34%? Show me the bonus impact."
- Scenario modeling for bonus optimization
"Analyze the last 3 months for OAK. What's the trend?"
- Month-over-month trend analysis with pattern identification
"Calculate bonuses if we hit all targets vs. current performance for White Buffalo."
- Potential vs. actual bonus comparison with opportunity cost
"Show me which category is costing us the most money across all locations."
- Cross-location variance analysis with dollar impact prioritization
"Break down the $14,832 E11even reimbursement impact on Cantina's liquor bonus tiers."
- Detailed reimbursement effect analysis with tier explanations
"What specific changes does each location need to unlock their next bonus tier?"
- Actionable recommendations with exact targets and dollar amounts
"Compare Cantina's September vs October and predict November performance."
- Trend analysis with forward-looking recommendations
"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:
- β Know exact bonus amounts in <2 minutes
- β Understand which categories need attention
- β Have clear action items for next month
- β 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:
Dual PDF Mode (Preferred) - If user uploads BOTH:
*foodUsageReport*.pdfAND*Gross*Sales*.pdf- Execute:
python3 pnl_analyzer_pdf.py foodUsage.pdf grossSales.pdf [reimbursement] - Result: Uses NET SALES - most accurate
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
CSV Mode (Legacy) - If user uploads:
*foodUsageReport*.csvAND*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
- β "Using NET SALES for accurate calculations" (dual PDF mode)
- β οΈ "Warning: Using GROSS SALES - upload Gross Sales PDF for better accuracy" (single PDF)
- π Show both total sales amounts and bonus difference when comparing modes