菜单
Use when analyzing which products make or lose money, ranking SKUs by margin or contribution, running a Pareto/80-20 on a product line, or deciding which SKUs to cut, reprice, or push in a product business.
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 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.
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.
| name | sku-profitability |
| description | Use when analyzing which products make or lose money, ranking SKUs by margin or contribution, running a Pareto/80-20 on a product line, or deciding which SKUs to cut, reprice, or push in a product business. |
Generated skill (example). This is the kind of bespoke skill
fpa-learn-businessproposes when the business profile says "product company with a discrete SKU set." It lives inskills/generated/- in a real engagement it would be written into the client's repo after human approval, citing the profile facts that justify it (here: a limited-SKU D2C brand where per-product economics drive the mix decision).
The channel-level forecast tells you the business is healthy; it doesn't tell you which products carry it. This skill computes per-SKU economics and the Pareto curve so you can see the 80/20, find margin-dilutive SKUs, and make cut/reprice/push calls.
Core principle: Revenue flatters; margin and contribution decide. Rank by gross profit, not by sales.
Load the SKUs (annual units, price, unit cost):
import pyfpa
skus = pyfpa.load_skus("examples/ridgeline/skus.yaml") # or build [Sku(...)] inline
df = pyfpa.sku_profitability(skus)
df is sorted by gross profit (desc), indexed by SKU, with columns: units, revenue, cogs, gross_profit, gross_margin, revenue_share, cumulative_revenue_pct.
Find the 80/20:
n = pyfpa.pareto_breakpoint(df, threshold=0.8) # SKUs that make 80% of revenue
Read the signals:
gross_margin - reprice or renegotiate cost; they're buying share with your margin.revenue_share AND low margin - candidates to cut (carrying cost without contribution).Recommend in business terms: which SKUs to push, reprice, or discontinue, and the margin impact of each move.
gross_margin here is per-unit price minus unit cost - it excludes channel fees, returns, and fulfillment. A D2C SKU and a wholesale SKU at the same listed margin are not equally profitable once channel economics hit.