SCF Deep Analysis

Controller-level Statement of Cash Flows deep analysis for QBO-connected clients. Computes CF Quality Ratio, Free Cash Flow, working capital movement drivers...

Security Scan

The instructions describe a QBO-focused cash‑flow analysis and expected local scripts and credentials, but the skill bundle includes no code, declares no required credentials, and leaves several execution details ambiguous — this mismatch is suspicious and worth verifying before use.

Purpose & Capability

The SKILL.md clearly requires a QBO connection, a QBO auth token, and a local Python script (scripts/pipelines/scf-deep-analysis.py) to run; the registry metadata declares no credentials, no code files, and no required env vars. That mismatch (a data‑sensitive integration that asks for tokens in docs but requests none in metadata) is inconsistent and unexplained.

Instruction Scope

Runtime instructions instruct pulling reports from QBO, P&L, GL vendor‑level transactions, reading/writing a cache path (.cache/scf-deep-analysis/{slug}.json), and writing an Excel workbook to disk (default ~/Desktop). The doc references a 'report {slug} cf' command and a local Python script — but does not define what CLI provides 'report', nor where the script comes from. Access to GL vendor transactions (potentially sensitive PII) and arbitrary cache files increases scope and sensitivity.

Install Mechanism

There is no install spec and no downloaded code included with the skill (instruction-only), which lowers installer risk. The SKILL.md does require openpyxl and Node.js be present, but no install steps are provided by the registry package itself.

Credentials

The documentation requires a 'QBO auth token configured' and a connected QBO client slug, but the skill metadata lists no required environment variables or primary credential. This omission is disproportionate and confusing for a skill that needs access to accounting data. The skill also reads a local cache path and writes output files, but those paths were not declared as required config access.

Persistence & Privilege

always is false and the skill does not request permanent platform presence. It does read and update a local cache (.cache/scf-deep-analysis) and writes reports to disk — normal for a pipeline — but any cached files could persist sensitive data between runs, so users should review the cache handling.

What to consider before installing

This skill's description and runtime instructions expect a local Python script, a QBO connection, and a QBO auth token, but the package you reviewed contains no code and declares no credentials. Before installing or running: (1) confirm you actually have the referenced repository/script (scripts/pipelines/scf-deep-analysis.py) from a trusted source; (2) ask the publisher to explain which CLI provides the undocumented 'report {slug} cf' command and why Node.js is required; (3) verify how QBO credentials should be provided and stored (the registry should declare required env vars); (4) test in a QBO sandbox and on non-production data first; (5) inspect any local cache (.cache/scf-deep-analysis) and output paths to ensure they don't leak client PII; and (6) request source code or a homepage from the publisher — if they cannot supply these or the discrepancies remain, treat the skill as untrusted.

SCF Deep Analysis — SKILL.md

What This Skill Does

Runs a controller-level Statement of Cash Flows deep analysis for a QBO-connected client. Extends the SCF Quick Compare with:

• CF Quality Ratio: Operating CF ÷ Net Income (>1.0 = cash-backed quality earnings)
• Free Cash Flow: Operating CF − CapEx (pulled from investing section)
• Working Capital Movement: AR, AP, Inventory, Prepaid — which WC components drove operating CF changes
• 3-Month Rolling Averages: Per-account and per-section CF trend baseline
• GL Drill-Down: Vendor-level transaction detail for every flagged CF account
• Controller Findings: Plain-English narratives with urgency — "Operating CF decreased 15% because AR increased $8K (collections lagging) while AP decreased $4K (paying faster)"
• Action Proposals: Specific, actionable recommendations (HIGH / MEDIUM / LOW urgency)
• CDC: Tracks what changed in CF since last run

Output: Excel workbook with 7 tabs: Summary | Detail | ⚠ Flags | GL Drill-Down | Working Capital Movement | Controller Findings | CDC Log

When To Use

• Monthly close: controller-level CF review beyond the Quick Compare
• Client with CF concerns (declining operating CF, negative FCF, low CF quality)
• Board prep: need to explain why cash changed this period
• Internal review: identify AR collection problems, AP timing, capex overruns

When NOT To Use

• Quick period-over-period CF snapshot → use scf-quick-compare.py instead
• P&L variance analysis → use pl-deep-analysis.py
• Budget vs. actual → use budget-vs-actual skill
• Non-QBO clients (no integration) → use bank-reconciliation skill

Prerequisites

• QBO client connected for the slug
• QBO auth token configured
• openpyxl installed: pip install openpyxl
• Node.js available on PATH

Script Location

scripts/pipelines/scf-deep-analysis.py

Usage

# Basic: current month vs. prior month (auto-calculated)
python3 scripts/pipelines/scf-deep-analysis.py \
  --slug my-client \
  --current-start 2026-03-01 --current-end 2026-03-31

# Explicit prior period
python3 scripts/pipelines/scf-deep-analysis.py \
  --slug my-client \
  --current-start 2026-02-01 --current-end 2026-02-28 \
  --prior-start 2026-01-01 --prior-end 2026-01-31

# YTD vs prior YTD
python3 scripts/pipelines/scf-deep-analysis.py \
  --slug my-client --ytd --year 2026

# Skip GL drill-down (faster — use when GL is unavailable or not needed)
python3 scripts/pipelines/scf-deep-analysis.py \
  --slug my-client \
  --current-start 2026-03-01 --current-end 2026-03-31 --skip-gl

# Custom output directory
python3 scripts/pipelines/scf-deep-analysis.py \
  --slug glowlabs \
  --current-start 2026-03-01 --current-end 2026-03-31 \
  --out ~/Desktop/reports

# Sandbox mode (QBO sandbox environment)
python3 scripts/pipelines/scf-deep-analysis.py \
  --slug glowlabs \
  --current-start 2026-03-01 --current-end 2026-03-31 --sandbox

Arguments

Argument	Required	Description
--slug	✅	Company slug (must match qbo-client connection)
--current-start	✅*	Current period start YYYY-MM-DD
--current-end	✅*	Current period end YYYY-MM-DD
--prior-start	❌	Prior period start — auto-calculated if omitted
--prior-end	❌	Prior period end — auto-calculated if omitted
--ytd	❌	YTD mode: Jan 1 → end of last completed month
--year	❌	Year for --ytd (default: current year)
--skip-gl	❌	Skip GL drill-down (faster run)
--out	❌	Output directory (default: ~/Desktop)
--sandbox	❌	Use QBO sandbox environment

*Required unless --ytd is used.

Pipeline Steps (8 Steps)

1. Pull CF — current + prior period CF from QBO via report {slug} cf
2. Pull P&L — current + prior period P&L for Net Income extraction (CF quality ratio)
3. Rolling Averages — pull 3 prior months of CF; compute per-account and per-section averages
4. CDC — compare current flat map vs. .cache/scf-deep-analysis/{slug}.json
5. CF Quality + FCF — compute ratio + extract CapEx from investing section
6. Working Capital Movement — classify AR / AP / Inventory / Prepaid from operating section
7. Variance + Flags + GL — flag material variances (≥10% or ≥$2,500); pull GL for flagged accounts
8. Controller Findings — generate narrative findings with urgency and action proposals

Output: Excel Workbook (7 Tabs)

Tab 1: Summary

• Section totals: Operating / Investing / Financing / Net Change / Beginning / Ending Cash
• vs. prior period + 3-month rolling average
• CF Quality Ratio block (with color coding)
• Free Cash Flow calculation
• Controller Findings summary (top 8 findings, HIGH in red)

Tab 2: Detail

• Every CF line item with prior period, current period, $ variance, % variance, rolling avg
• Section-grouped with color bands (Operating = blue, Investing = yellow, Financing = purple)
• F/U column (Favorable = more cash, Unfavorable = less cash)

Tab 3: ⚠ Flags

• Material variances only: ≥10% change OR ≥$2,500 absolute delta
• Includes rolling avg comparison
• Sorted by absolute dollar variance

Tab 4: GL Drill-Down

• Vendor-level transaction detail for every flagged account
• Top 3 vendor contributors shown in sub-header per account
• Max 50 transactions per account
• Skipped if --skip-gl flag used

Tab 5: Working Capital Movement

• AR, AP, Inventory, Prepaid, Other WC — current vs. prior vs. delta
• Cash Impact column (Source / Use)
• Plain-English analysis note per component (e.g., "AR increased $8K — collections lagging sales")
• Total WC impact row

Tab 6: Controller Findings

• Full narrative findings sorted HIGH → MEDIUM → LOW
• Detail / GL attribution per finding
• Specific recommended action per finding
• $ Impact column

Tab 7: CDC Log

• All accounts/line items that changed vs. last cached run
• Prior value, current value, $ delta, % change, note (New / Changed / Removed)
• Color coded: green = cash increased, red = cash decreased

Cache

.cache/scf-deep-analysis/{slug}.json

Stored after each run. Contains:

• flat_map — all CF line items and amounts
• totals — section totals (operating, investing, financing, net_change, ending_cash)
• cf_quality — CF quality label
• fcf — Free Cash Flow amount
• net_income — Net Income for the period
• saved_at — ISO date of last run

Key Metrics Explained

CF Quality Ratio

Operating CF / Net Income

Ratio	Quality	Color
≥ 1.0x	✅ Quality Earnings — cash-backed	Green
0.5–1.0x	⚠ Adequate — partially cash-backed	Yellow
< 0.5x	⚠ Low Quality — accrual-heavy	Orange
< 0	🔴 Cash Drain — cash negative despite reported profit	Red

Free Cash Flow

FCF = Operating CF + CapEx (CapEx is negative outflow, so this subtracts it)

CapEx detected by keyword matching in investing section (equipment, property, asset, capital expenditure, etc.)

Working Capital Movement (in Operating section)

• AR change (negative = AR grew = cash used; positive = AR shrank = cash released)
• AP change (positive = AP grew = cash deferred; negative = AP shrank = cash paid out)
• Inventory change (negative = inventory built = cash used; positive = inventory drawn = cash released)
• Prepaid change (negative = more prepaid = cash used; positive = prepaid expensed = cash released)

Materiality Thresholds

• Percent threshold: ≥10% change in any CF line item
• Absolute threshold: ≥$2,500 absolute variance
• Both thresholds checked — either triggers a flag

Safety Rules

• Read-only: No writes to QBO — only pulls reports
• All Decimal math: No floating-point for financial calculations
• Disclaimer footer: Controller Findings tab includes audit disclaimer
• Cache separation: Uses .cache/scf-deep-analysis/ — separate from scf-quick-compare cache

Related Pipelines

Pipeline	Use When
scf-quick-compare.py	Quick CF period-over-period snapshot (4 tabs, no GL)
scf-deep-analysis.py	Controller-level CF with GL drill-down, CF quality, FCF, WC movement
pl-deep-analysis.py	Same depth for P&L (not CF)
budget-builder.py	Build annual CF budget / BvA