# Ivx Ams Finance Ops

> AI CFO briefings from QuickBooks exports, burn/runway, scenario modeling, and build-cost estimates. Use for CFO briefing, runway analysis, or development cost estimates.

- Skill: `intelli-verse-x/ivx-ams-finance-ops` (Agent Skill, multi-file: 14 files)
- Install (CLI): `npx skillmds add intelli-verse-x/ivx-ams-finance-ops`
- Raw SKILL.md: https://api.skillmd.com/api/skills/intelli-verse-x/ivx-ams-finance-ops/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: intelli-verse-x (https://skillmd.com/u/intelli-verse-x)
- Updated: 2026-08-19
- Page: https://skillmd.com/skills/intelli-verse-x/ivx-ams-finance-ops

---



## Working directory

```bash
cd ~/.cursor/skills/ams-finance-ops
# Windows: cd $env:USERPROFILE\.cursor\skills\ams-finance-ops
```
## Cursor install notes

- Skill root: this folder (scripts + references live here).
- Vendor source: `~/.cursor/skills/_vendor/ai-marketing-skills/` (git pull to update).
- Telemetry is optional; skip `telemetry/*.py` unless you opt in.
- Run Python from this skill directory so relative paths resolve.
- Prefer `python` on Windows if `python3` is missing.

## Tool 1: CFO Briefing Generator

Generate executive financial summaries from QuickBooks exports.

### Workflow

#### 1. Ingest Files

Place QuickBooks export files (CSV, XLSX, XLS) in a working directory. Accepted report types (any subset works — P&L alone is sufficient):

- **P&L Summary** — Revenue, COGS, expenses, net income (MOST IMPORTANT)
- **P&L by Customer** — Revenue breakdown by client
- **P&L Detail** — Transaction-level detail (XLSX)
- **Balance Sheet** — Assets, liabilities, equity
- **General Ledger** — All account transactions
- **Expenses by Vendor** — Vendor-level expense breakdown
- **Transaction List by Vendor** — Detailed vendor transactions
- **Bill Payments** — AP payment history
- **Cash Flow Statement** — Operating/investing/financing flows (XLSX)
- **Account List** — Chart of accounts

#### 2. Run Analysis

```bash
python3 scripts/cfo-analyzer.py --input ./data/uploads/ [--period YYYY-MM]
```

Options:
- `--input DIR` — Directory with QB exports
- `--period YYYY-MM` — Override period label (default: auto-detected from files)
- `--history DIR` — History directory for MoM comparison (default: `./data/history/`)
- `--no-history` — Skip saving to history

The script:
1. Auto-detects file types by scanning headers
2. Parses each file into structured data
3. Computes all KPIs (see `references/metrics-guide.md` for definitions and healthy ranges)
4. Loads prior period from history for MoM comparison
5. Saves current period to history
6. Outputs formatted executive summary to stdout

#### 3. Scenario Modeling (Optional)

After running the CFO analysis, model base/bull/bear scenarios:

```bash
python3 scripts/scenario-modeler.py --input ./data/financial-latest.json
```

This generates 12-month projections for:
- **Base case** — current trajectory continues
- **Bull case** — growth targets met (new product revenue + new clients)
- **Bear case** — lose top clients

#### 4. Deliver Summary

The script outputs a formatted briefing with emoji status indicators (🟢🟡🔴), suitable for Slack, email, or any messaging surface.

### File Format Details

See `references/quickbooks-formats.md` for expected CSV/XLSX column formats and detection heuristics.

### Metric Thresholds

See `references/metrics-guide.md` for healthy ranges, red/yellow/green thresholds, and benchmark context. Adjust thresholds for your business size and type.

## Tool 2: Codebase Cost Estimator

Estimate full development cost of a codebase.

### Workflow

#### Step 1: Analyze the Codebase

Read the entire codebase. Catalog total lines of code by language/type, architectural complexity, advanced features, testing coverage, and documentation quality.

#### Step 2: Calculate Development Hours

Apply productivity rates from `references/rates.md`. Calculate base hours per code type, then apply overhead multipliers for architecture, debugging, review, docs, integration, and learning curve.

#### Step 3: Research Market Rates

Use web search to find current hourly rates for the relevant specializations. Build a rate table with low / median / high for the project's tech stack.

#### Step 4: Calculate Organizational Overhead

Convert raw dev hours to calendar time using efficiency factors from `references/org-overhead.md`. Show estimates across company types (Solo through Enterprise).

#### Step 5: Calculate Full Team Cost

Apply supporting role ratios and team multipliers from `references/team-cost.md`. Show role-by-role breakdown, plus summary across all company stages.

#### Step 6: Generate Cost Estimate

Output the full estimate using the template in `references/output-template.md`. Include all sections: codebase metrics, dev hours, calendar time, market rates, engineering cost, full team cost, grand total summary, and assumptions.

#### Step 7: AI ROI Analysis (Optional)

If the codebase was built with AI assistance, calculate value per AI hour using `references/claude-roi.md`. Determine active hours via git history clustering, calculate speed multiplier vs human developer, and compute cost savings and ROI.

### Key Principles

- Present professionally, suitable for stakeholders
- Include confidence level (low/medium/high) and key assumptions
- Highlight highest-complexity areas that drive cost
- Always show ranges (low/avg/high), never a single number
- Search for CURRENT year market rates, don't use stale data