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Use when building a new openfpa forecast model from a company's financials - a trial balance, a P&L export, or a pasted income statement - and you need a runnable config to exist before any forecasting or analysis.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use when the user wants their model in Excel with real working formulas - "export this to Excel", "a workbook I can hand my board", "something that recalculates when I change an assumption". Produces a live-formula workbook generated from the model structure and verified against the engine before delivery.
Use when producing a board deck, investor update, or CFO briefing from an openfpa forecast - turning model output into a board-ready narrative and exportable artifacts.
Use when modeling a multi-segment company that discloses segment net sales and segment Adjusted EBITDA (ASU 2023-07) but not segment COGS or operating income - rolls segment P&Ls into a consolidated forecast and reconciles total segment Adjusted EBITDA to the disclosed total. Generated for Fox Factory (PVG/AAG/SSG).
Use when you want the model to learn from how its past forecasts actually turned out - scoring forecasts against the company's real actuals, backtesting assumptions on history, and proposing ratified improvements. Runs at/after monthly close.
Use when a human reviewing a forecast catches something off ("December always spikes", "you're double-counting deferred revenue", "that Q3 number was a one-time contract") - captures it as a durable, typed correction in the company's memory so future forecasts are grounded by it.
Use when answering "when do we run out of cash", building a 13-week cash forecast, sizing a credit line, or analyzing near-term liquidity and payment timing in openfpa.
| name | fpa-scaffold-model |
| description | Use when building a new openfpa forecast model from a company's financials - a trial balance, a P&L export, or a pasted income statement - and you need a runnable config to exist before any forecasting or analysis. |
Turn a company's financials into a runnable pyfpa config. Read the business profile first (see fpa-learn-business), infer the chart-of-accounts → model-line mapping, and write a validated EntityConfig YAML following openfpa conventions. Output a runnable skeleton plus an explicit list of assumptions to confirm.
Core principle: Convention over invention. Map the real numbers onto the existing engine shape; don't design a new one.
.fpa/business-profile.md existspyfpa.read_pl_csv(path) (or a pyfpa.io.adapters source) → {account: amount}.EntityConfig schema:
channels[] (one Channel per channel/segment, with annual_revenue, a 12-month seasonality weight list, growth_rate, cogs_pct)opex[] as OpexLine(kind="fixed", monthly_amount=…) or kind="variable", pct_of_revenue=…debt[] (term_loan with monthly_principal, or interest-only loc)working_capital(dso_days, dpo_days, dio_days) and opening_balancesmodels/generated/. Validate
config with pyfpa.load_config(path), which raises on any bad field.python3 models/generated/run_forecast.py. Keep the runner thin and make its
output locations explicit.openfpa entrypoint-register, including
its inputs and outputs. Registration publishes the command for agent
discovery; it does not run it.opening_balances AR/AP/inventory to the first forecast month's DSO/DPO/DIO-implied balances - the engine diffs each month against the prior, seeding month 1 against opening, so use month-1 projected revenue/COGS, NOT the annual average. Get this wrong and month-1 cash swings on a one-time artifact (see fpa-cfo-judgment working-capital seam)."total" is a reserved channel/opex name (the engine adds a total column).A live-formula Excel edition of the model is available via fpa-excel-model.
Runnable config confirmed → fpa-configure-actuals to wire live/real numbers, then the operate skills.