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Strategic advisory for e-commerce founders on unit economics, fulfillment models, payments, and channel strategy.
Passed 14 of 22 test cases with the skill, and 6 of 22 without it.
and 5 more in the full report
8 fixed6 passed either way8 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
I have prepared a JSON configuration file named `brand_inputs.json` containing COGS, fulfillment, payment processing, and ad spend. What exact terminal command line invocation runs the unit economics calculator tool and produces JSON formatted output?
| Checked | Without skill | With skill |
|---|---|---|
| specifies the command python scripts/ecom_unit_economics_calculator.py brand_inputs.json --json | Missed | Passed |
| includes the --json flag in the command execution | Passed | Passed |
The instructions your model reads when the skill loads.
Strategic frameworks for e-commerce founders, operators, and brand builders. Most ecommerce decisions are unit-economics decisions — knowing the math is the difference between a brand that compounds and one that subsidizes itself out of existence.
ecommerce, e-commerce, DTC, direct-to-consumer, Shopify, Amazon, retail, wholesale, 3PL, fulfillment, dropship, unit economics, contribution margin, CAC, AOV, LTV, returns, refunds, payment processing, interchange
Before building the model, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the model.
python scripts/ecom_unit_economics_calculator.py model.json
Calculates gross margin, contribution margin, CAC payback, and per-order profit from a structured input file.
python scripts/ecom_unit_economics_calculator.py model.jsontest cases passed, vs 6 / 22 without
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