finance-ops

Convert QuickBooks CSV/XLSX exports into executive CFO briefings with scenario projections.

3.3k|656|Updated Mar 28, 2026
One-click install
npx skills add https://github.com/ericosiu/ai-marketing-skills --skill finance-ops
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: finance-ops
Source: https://github.com/ericosiu/ai-marketing-skills/tree/main/finance-ops
Command: npx skills add https://github.com/ericosiu/ai-marketing-skills --skill finance-ops

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, openpyxl, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill removes the guesswork from finance reviews by turning messy QuickBooks exports into an executive-ready CFO briefing, including margin health, anomalies, burn/runway signals, and actionable scenarios.

Core Features & Use Cases

  • QuickBooks → executive CFO briefing: Ingests P&L, Balance Sheet, General Ledger, Cash Flow, expenses by vendor, and vendor transaction lists to produce a structured summary with traffic-light (🟢/🟡/🔴) indicators.
  • Anomaly detection & operational insights: Highlights notable expense spikes, vendor/subscription bloat, recruiting/owner-related spend, and top customer concentration risk.
  • Scenario modeling for next 12 months: Generates base/bull/bear projections to estimate burn, breakeven direction, and the cost/revenue levers implied by the data.
  • Codebase cost estimation (optional): Estimates full development effort and cost for a codebase, including organizational overhead and AI ROI analysis.
  • Use case: Feed your latest QuickBooks CSV/XLSX exports to identify why margins dropped last month, what costs changed, which vendors drove the movement, and what financial outcome different growth or churn scenarios imply.

Quick Start

Give the AI Codebase the finance-ops skill and run CFO analysis against your QuickBooks export folder so it prints an executive CFO briefing to the terminal.

Frequently Asked Questions about finance-ops

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate an executive CFO briefing from QuickBooks CSV exports?

To generate an executive CFO briefing from QuickBooks CSV exports, provide your P&L, Balance Sheet, and Cash Flow files to automatically compute profitability health, detect expense anomalies, and model 12-month base/bull/bear scenarios with traffic-light indicators.

What financial KPIs and anomalies can I detect from QuickBooks report exports?

Financial anomaly detection from QuickBooks exports highlights expense spikes, vendor bloat, recruiting spend, top customer concentration risk, and burn rate signals by computing KPI thresholds with prior-period MoM comparison for stakeholder-ready summaries.

Can I use Excel XLSX files for scenario modeling and burn rate analysis?

Yes, you can use XLSX files for scenario modeling and burn rate analysis. The system parses supported QuickBooks report types in both CSV and XLSX formats to generate base/bull/bear projections estimating breakeven direction and cost/revenue levers.

Does this tool require pandas and openpyxl to parse QuickBooks reports?

Yes, parsing QuickBooks reports requires pandas and openpyxl dependencies to ingest CSV and XLSX exports, compute MoM KPI comparisons, and output structured CFO summaries with optional 12-month scenario projections.

What's the best way to estimate codebase development cost with organizational overhead?

Codebase cost estimation with organizational overhead applies AI ROI analysis to estimate full development effort and cost, integrating financial data assumptions to produce cost projections alongside standard QuickBooks financial briefings.

When should I not use automated scenario modeling for monthly finance reviews?

Automated scenario modeling is not suited for contexts outside services or agency monthly finance reviews, as the KPI thresholds and burn rate signals specifically parse QuickBooks report types and compute prior-period MoM comparisons for those operational structures.