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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.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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.