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🦀 ClawHub

Cash Flow Forecast

by @samledger67-dotcom

Generates a 13-week rolling cash flow forecast from QuickBooks Online data with base, optimistic, and pessimistic scenarios including burn rate and runway an...

Versionv1.0.2

Downloads590

Installs1

#legal

View on ClawHub →

TERMINAL

clawhub install cash-flow-forecast

📖 About This Skill

name: cash-flow-forecast description: "Build a 13-week rolling cash flow forecast from QBO data with 3-scenario modeling (base, upside, downside). Pulls Balance Sheet and CF Statement for starting cash and trend baseline. Use when a client needs cash runway projection, burn rate analysis, or scenario-based liquidity planning. NOT for annual budgets, P&L variance analysis, or bank reconciliation." license: MIT summary: - Builds a 13-week rolling cash flow forecast from QBO data with 3-scenario modeling - Pulls live Balance Sheet (starting cash) + CF Statement (trend baseline) from QBO - Outputs Excel: Summary | Weekly Detail | Scenarios | Burn Rate | Assumptions | CDC Log - GlowLabs-type clients: runway/burn emphasis; SB Paulson-type: interest expense emphasis - CDC tracks forecast accuracy vs. prior runs (predicted vs. actual starting cash) updated: 2026-03-17 metadata: openclaw: emoji: "💸"

Cash Flow Forecast Skill

When to Use

Client asks for a 13-week (or rolling n-week) cash flow forecast

Need to project runway for a high-burn client (GlowLabs-type)

Monthly or quarterly cash flow advisory deliverable

Any time cash position monitoring or scenario modeling is needed

SOP for the client marks "Cash Flow Forecast: ✅"

NOT for

Historical cash flow analysis (use P&L Deep Analysis pipeline)

Bank reconciliation (use bank-reconciliation.py)

Full audit of cash flows (use QBO CF report directly)

Balance sheet projections / full financial models

Script Location

scripts/pipelines/cash-flow-forecast.py

Quick Start

cd /Users/samshouse/.openclaw/workspace
Standard 13-week forecast
python3 scripts/pipelines/cash-flow-forecast.py --slug glowlabs
6-month history for better seasonality
python3 scripts/pipelines/cash-flow-forecast.py --slug sb-paulson --months 6
Custom low-cash threshold (GlowLabs: high burn)
python3 scripts/pipelines/cash-flow-forecast.py --slug glowlabs \
    --low-cash-threshold 50000 \
    --critical-threshold 25000 \
    --out ~/Desktop/reports
Sandbox testing
python3 scripts/pipelines/cash-flow-forecast.py --slug glowlabs --sandbox

All CLI Options

| Flag | Default | Description | |------|---------|-------------| | --slug | required | QBO company slug | | --weeks | 13 | Forecast horizon (weeks) | | --months | 3 | Months of CF history to pull (1–6) | | --low-cash-threshold | 25000 | Warn when balance < X | | --critical-threshold | 10000 | Critical alert when balance < X | | --account | auto | Specific bank account name filter | | --out | ~/Desktop | Output directory | | --sandbox | false | Use QBO sandbox |

Output Excel Tabs

Tab 1: Cash Flow Summary

Current cash position (all bank/cash accounts from Balance Sheet)

13-week KPI summary: total inflows, outflows, net flow, end balance

Burn rate and runway in callout box

Full weekly trajectory table with alert coloring

SOP notes printed at top (client-specific warnings)

Tab 2: Weekly Detail

Matrix: each row = a CF subcategory, each column = a week

Inflows section (green) → Outflows section (red)

Subtotals, Net Flow row, Running Balance row

Alert coloring: yellow = warn, orange/red = critical

Tab 3: Scenarios

Side-by-side: Base | Optimistic | Pessimistic

12 KPI rows: inflows, outflows, net, end balance, burn, runway, alert weeks

Weekly balance comparison table across all 3 scenarios

Best/Worst delta and % spread columns

Tab 4: Burn Rate

Detailed burn metrics (base case)

Runway comparison table (all 3 scenarios)

Week-by-week burn trend

🔴 High burn emphasis for GlowLabs-type clients

Tab 5: Assumptions

All parameters used (thresholds, adjustments, seasonality weights)

Monthly averages per category (the baseline used)

Client SOP config summary

Methodology notes

Tab 6: CDC Log

Run-over-run changes: starting cash, burn rate, runway

Forecast accuracy: compares prior-run predicted starting cash vs. actual

First run: saves baseline; second+ run shows deltas

Scenario Definitions

| Scenario | Collections | Expenses | |----------|-------------|----------| | Base | Historical avg | Historical avg | | Optimistic | +10% | Unchanged | | Pessimistic | -15% | +5% |

Cash Flow Categories

Automatically classified from QBO CF rows:

Operating — Inflows

collections: Revenue, AR, Net Income, payment processor receipts

interest: Interest income

Operating — Outflows

payroll: Wages, salaries, officer comp, Deel (GlowLabs)

rent: Rent, lease, occupancy

vendors: AP, COGS, professional fees, software, subscriptions

interest: Interest expense (SB Paulson: material line)

taxes, insurance

Investing

capex: Equipment, property, asset purchases

Financing

debt: Loans, line of credit, notes payable

equity: Owner distributions/contributions

safe: SAFE notes (GlowLabs)

Client SOP Integration

The script reads clients/{slug}/sop.md automatically and adjusts:

| SOP Signal | Effect | |------------|--------| | "burn rate", "runway", "high cash burn" | Burn Rate tab emphasized, 🔴 alert | | "interest expense" | Interest tracked separately | | "POS collection", "collected at POS" | No AR lag — flat weekly inflow distribution | | "accounts receivable" | AR-based: note 30-45 day receipt lag | | "SAFE" | SAFE financing category added | | "crypto", "wallet", "ETH" | Crypto wallet note added | | "Deel" | Deel inbound classified as expense reduction |

Seasonality Weights

Default week-of-month distribution (configurable in script CONFIG section):

| Week | Inflows | Outflows | Rationale | |------|---------|----------|-----------| | Week 1 (days 1–7) | 30% | 35% | Collections/payroll land early | | Week 2 (days 8–14) | 20% | 20% | Mid-month quiet | | Week 3 (days 15–21) | 20% | 25% | Mid-month payroll + rent | | Week 4 (days 22–28) | 30% | 20% | End-month collections | | Week 5 (overflow) | 0% | 0% | Rarely used |

POS clients (e.g. SB Paulson): inflows flattened to equal weekly distribution.

CDC Accuracy Loop

1. First run: saves starting_cash, first_week_balance, avg_monthly_burn, months_of_runway 2. Second run: compares new starting_cash against prior first_week_balance 3. Accuracy % = how close the forecast was to reality 4. Burn rate and runway deltas tracked run-over-run 5. Cache stored in .cache/cash-flow-forecast/{slug}.json

Low-Cash Alert Colors

| Color | Excel Fill | Condition | |-------|-----------|-----------| | ✅ OK | White | Balance ≥ low threshold | | ⚠ Warn | Yellow | Balance < $25K (configurable) | | 🔴 Critical | Orange/Red | Balance < $10K (configurable) |

Client-Specific Notes

GlowLabs (High Burn)

--low-cash-threshold 50000 --critical-threshold 25000 recommended

SOP auto-detected: burn rate tab emphasized with red header

SAFE financing and Deel categories auto-classified

Runway is the #1 KPI — shown prominently in Summary tab

SB Paulson / Willo Salons

--months 6 for better seasonality (salon business is seasonal)

POS collection = no AR lag; inflows distributed flat across weeks

Interest expense tracked as separate operating outflow category

Cash Flow Forecast frequency: quarterly advisory (per SOP)

Dependencies

pip install openpyxl

Node.js QBO client must be authenticated with a valid token.

Output Naming

CashFlowForecast_{slug}_{YYYY-MM-DD}.xlsx Default output: ~/Desktop/

Related Pipelines

pl-quick-compare.py — P&L variance analysis

pl-deep-analysis.py — Controller-level with GL drill-down

bank-reconciliation.py — Bank statement reconciliation

⚡ When to Use

Trigger	Action
- Need to project runway for a high-burn client (GlowLabs-type)
- Monthly or quarterly cash flow advisory deliverable
- Any time cash position monitoring or scenario modeling is needed
- SOP for the client marks "Cash Flow Forecast: ✅"

💡 Examples

cd /Users/samshouse/.openclaw/workspace
Standard 13-week forecast
python3 scripts/pipelines/cash-flow-forecast.py --slug glowlabs
6-month history for better seasonality
python3 scripts/pipelines/cash-flow-forecast.py --slug sb-paulson --months 6
Custom low-cash threshold (GlowLabs: high burn)
python3 scripts/pipelines/cash-flow-forecast.py --slug glowlabs \
    --low-cash-threshold 50000 \
    --critical-threshold 25000 \
    --out ~/Desktop/reports
Sandbox testing
python3 scripts/pipelines/cash-flow-forecast.py --slug glowlabs --sandbox