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Pricing One Pager
Generates data-driven pricing proposals (list, pack, floor) based on unit economics and sourced willingness-to-pay.
$19
Pricing One Pager
Example session with this skill installed
Create a pricing one-pager for 'API Proxy' at 50,000 units/mo. Costs from docs/unit-economics.md (dated 2023-10-01). Willingness is $0.05/unit per customer quote 2023-11-15. Use variable floor.
- Read your context and instructions
- Compiled the pricing one pager
- Generated the document
I have generated the pricing proposal for API Proxy based on the provided unit economics and willingness-to-pay data. The model uses a variable cost floor as requested and validates all pricing against this limit.
Pricing Proposal: API Proxy
Product: API Proxy
Unit: request
Volume: 50,000 / month
Rates As Of: 2023-10-01
Currency: USD
Status: ready
Not tax, legal, or investment advice.
Costs
- Full Cost per Unit: 0.0350 (Copied from docs/unit-economics.md)
- Variable Cost per Unit: 0.0210 (Copied from docs/unit-economics.md)
- Monthly Cost: 1,750.00 (0.0350 * 50,000)
Willingness
- Per Unit: 0.0500
- Source: buyer quote
- Date: 2023-11-15
Prices
- Floor Unit: 0.0210 (Rule: variable)
- List Unit: 0.0500
- Pack Price: unset (No pack units specified)
- Pack Floor: unset
- Contribution: 0.0150 (0.0500 - 0.0350)
- Monthly at List: 2,500.00 (0.0500 * 50,000)
Caveats
- No charm rounding applied; list matches sourced willingness exactly.
- House store account names and processor IDs were excluded.
Residuals
- filed: no
- priced: proposed
- published: no
- advised: no
- floor_status: floor is variable; full cost is higher
Next steps
- Review the
docs/pricing.mdfile for arithmetic verification. - Determine if a pack size (pack_units) should be added to the model.
- Use the
tco-comparisonskill if you need to compare this against competitor pricing.
pricing-one-pager.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
Setting product prices often involves guesswork or "charm" rounding that ignores the underlying unit economics. This leads to selling packs at a loss or setting list prices that fall below the actual cost floor.
What it does
- Calculates a hard price floor based on full or variable unit costs.
- Proposes list and pack prices derived strictly from sourced willingness-to-pay data.
- Validates pack discounts to ensure they never dip below the calculated floor.
- Generates a structured
docs/pricing.mdone-pager with replayable arithmetic. - Refuses "charm rounding" or arbitrary discounts that violate margin constraints.
Frameworks & tools
This skill is framework-agnostic. It requires an agent capable of file system operations (read/write) and basic arithmetic via Python or a standard calculator tool.
Why this beats prompting it yourself
Generic prompts often hallucinate "standard" margins or suggest "nice" numbers like $9.99 that might be unprofitable. This skill enforces strict data binding, requiring dated evidence for costs and willingness, and automatically blocks the workflow if profitability rules are violated.
Use cases
- Determining the minimum viable price for a new digital service or physical unit.
- Validating if a proposed bulk discount remains profitable at current monthly volumes.
- Creating a standardized pricing proposal for stakeholder review.
- Auditing current list prices against updated unit economics.
Known limitations
Does not handle multi-product bundles, tax calculations, or store-front publishing. Requires pre-existing unit cost data.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
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Click the path to copy it. Create the folder if it does not exist yet.
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