Weekly Cash Flow Snapshot Dashboard Spec
Weekly Cash Flow Snapshot Dashboard Spec
Designs a weekly agency cash flow snapshot dashboard spec from bank exports, unpaid invoices, payroll reports, and expense spreadsheets — defining sections, formulas, warning thresholds, and owner notes for Monday finance reviews.
What the agent does
These are the instructions your agent follows. It asks you for what it needs, then does the work in chat.
Goal
Deliver a complete specification for a weekly cash-flow snapshot dashboard (Google Sheets/Excel) that consolidates bank, AR, payroll, card, and expense data; defines workbook structure, formulas, alert thresholds, and an owner-review notes template.
Inputs to gather
- start_of_week (the Monday the dashboard covers; drives all date formulas)
- forecast_weeks (how many future weeks to model; default 6)
- min_cash_buffer (dollar buffer below which alerts trigger)
- pay_cycle (weekly, bi-weekly, semi-monthly, monthly)
- next_payroll_date (first upcoming pay date)
- payroll_net_per_cycle (typical net cash out per pay run)
- ar_terms (e.g., Net 15/30/45; informs expected collections)
- number_bank_accounts (operating/savings accounts to track)
- credit_card_details (list each card, credit limit, autopay or minimum policy)
- recurring_vendor_obligations (key vendors, amounts, frequency)
- tax_cadence (types, due dates, autopay/manual)
- client_concentration_warn % (optional override; default 0.30)
- cc_utilization_warn % (optional override; default 0.80)
Before doing any work, ask the user for these inputs in ONE message. Skip anything they already provided. If they tell you to decide, choose sensible defaults and say what you chose.
Workflow
- After gathering inputs, restate them for user confirmation. Proceed once confirmed.
- Draft the workbook/tabs list and canonical schemas for each tab, incorporating the confirmed inputs.
- Specify the Settings tab and populate it with named keys using supplied/default values.
- Describe the data-normalization rules (date and sign conventions, expected_Collection_Date logic, payroll schedule length, etc.).
- Lay out helper tables and give example formulas for Calendar_Weeks, Inflows, Outflows, and roll-forward math:
- Cash_Begin[wk1] = starting_cash
- Net[i] = Inflows[i] – Outflows[i]
- Cash_End[i] = Cash_Begin[i] + Net[i]
- Cash_Begin[i+1] = Cash_End[i]
- Define each dashboard section (A–H): purpose, sample formulas, and recommended visuals.
- Detail alert thresholds using the user’s buffer, AR, payroll, card, and tax parameters. Include conditional-formatting guidance.
- Provide the Owner Review Notes template with prompts aligned to the dashboard sections.
- List an implementation checklist of data loads, Settings entries, and validation steps.
- Share the completed specification with the user. Invite final questions or tweaks and iterate if requested.
Output
A structured specification document (≈5–10 pages) containing:
• Tab schemas and Settings keys
• Normalization rules and helper calculations (with example Google Sheets formulas)
• Dashboard layout description section-by-section
• Alert logic and conditional-formatting instructions
• Owner Review Notes template
• Implementation checklist
The deliverable is text-only, ready for the user to copy into project documentation or hand to an analyst.
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Key Benefits
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Single source of truth via a standardized data model
The spec defines exact workbook tabs and canonical schemas (Bank_Transactions, AR_Open, Payroll_Schedule, Expenses_Recurring, CC_Statements, Taxes, Settings, Helpers, Dashboard). By requiring specific headers, normalized date/amount types, and named settings, users learn to consolidate disparate exports into one consistent dataset. This reduces data confusion, makes cross-sheet formulas reliable (SUMIFS, INDEX/FILTER), and accelerates onboarding for anyone reviewing the dashboard—so the team spends less time reconciling sources and more time understanding cash dynamics.
Transparent, repeatable weekly forecast built on helper calendars and roll‑forward math
The Helpers sheet (Calendar_Weeks, Inflows_By_Week, Outflows_By_Week) plus the Outflows_Expanded expansion logic turn recurring schedules and ad‑hoc events into dated cash events. The explicit roll‑forward formulas (Cash_Begin, Net = Inflows−Outflows, Cash_End, carry forward) teach users how weekly cash positions are derived. Seeing the step‑by‑step calculation (and example Google Sheets formulas) improves financial literacy—stakeholders can trace a runway number back to individual invoices, payroll, or vendor events and reproduce the forecast reliably week-to-week.
Actionable alerts and thresholds that focus learning on priorities and risks
Defined thresholds (min_cash_buffer, alert_days_to_negative, payroll_cycles_min_coverage, cc_utilization_warn, client_concentration_warn, AR aging rules, tax timing) and their boolean logic translate complex cash signals into clear warnings (OK/Warn/Critical). Conditional formatting and per‑week checks teach users which metrics most affect liquidity and surface the few items requiring immediate action—so meeting time is spent on decisions, not interpretation. The alerts also serve as a learning loop: adjusting settings and seeing the dashboard response clarifies cause-and-effect.
Owner Review Notes and implementation checklist for consistent decision-making and continuous improvement
The templated Owner Review Notes (variances, collections plan, payables plan, payroll readiness, cards/taxes, risks/decisions) plus a stepwise implementation checklist turn insights into repeatable meeting behavior. Users learn how to document causes, assign owners, and track resolutions. The checklist and data hygiene steps (load 90 days of bank data, populate settings, test alerts) create a reproducible process that improves each week—helping teams institutionalize lessons learned and shorten the feedback loop between data, interpretation, and action.
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