Pricing Optimizer logo

Pricing Optimizer

Organization
openaccountant
pricing-optimizer

Analyze pricing against costs and margins to optimize profitability.

Overview

Publisheropenaccountant
Repositoryskills
Skill namepricing-optimizer
Stars
106
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by openaccountant on GitHub. Read the source before you install it.

Installation

Install the Pricing Optimizer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/openaccountant/skills/tree/main/business/pricing-optimizer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/openaccountant/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/business/pricing-optimizer .claude/skills/pricing-optimizer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pricing Optimizer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pricing Optimizer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pricing Optimizer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Pricing Optimizer

Overview

Compare your current pricing against actual costs to calculate true margins per product or service. Identifies underpriced offerings, estimates the revenue impact of price adjustments, and suggests target pricing based on desired margin.

Wilson Tools Used

  • spending_summary — calculate COGS and direct costs per category to determine cost basis
  • transaction_search — pull revenue by product or service line, identify transaction volumes and average transaction size

Workflow

  1. Ask for the analysis period and list of products/services offered (or detect from transaction categories).
  2. Use transaction_search to find all revenue transactions, grouped by product/service type.
  3. Calculate: average sale price, total units sold, total revenue per offering.
  4. Use spending_summary to identify direct costs associated with each product/service.
  5. Calculate per-offering economics:
PRICING ANALYSIS — [Period]
════════════════════════════════════════════════════════════
Product/Service    Avg Price   Unit Cost   Margin   Volume   Revenue
────────────────────────────────────────────────────────────────────
Web Design Pkg      $3,000      $1,200      60%       8     $24,000
Monthly Retainer    $1,500        $900      40%      12     $18,000
Logo Design           $500        $350      30%      15      $7,500
Rush Projects       $2,000      $1,600      20%       5     $10,000
────────────────────────────────────────────────────────────────────
  1. Flag offerings with margins below 40% as candidates for price increases.
  2. For each underpriced offering, calculate the target price for a desired margin:
    • Target Price = Unit Cost / (1 - Desired Margin)
    • Example: $350 cost, 50% target margin = $350 / 0.50 = $700
  3. Estimate revenue impact of price changes assuming 0-10% volume loss per 10% price increase.
  4. Rank offerings by total profit contribution (margin * volume) to prioritize optimization effort.

Without Wilson

  1. Create a spreadsheet with columns: Product/Service, Price Charged, Direct Cost, Units Sold.
  2. Direct Cost includes materials, labor hours * hourly rate, software, and any cost that only exists because of this product.
  3. Unit Margin: =Price-DirectCost. Margin %: =UnitMargin/Price*100.
  4. Total Profit: =UnitMargin*UnitsSold.
  5. Target Price at desired margin: =DirectCost/(1-DesiredMarginPercent).
  6. Revenue Impact estimate: =NewPrice*UnitsSold*0.95 (assuming 5% volume drop per 10% price increase — adjust based on your price sensitivity).
  7. For services billed hourly, calculate your effective rate: =TotalClientPayments/TotalHoursWorked. Compare to market rates on Glassdoor, Upwork, or industry salary surveys.
  8. Use the pricing calculator at priceintelligently.com or profitwell.com/tools for SaaS-specific analysis.

Important Notes

  • Cost-plus pricing (cost + desired margin) is a floor, not a ceiling. Value-based pricing often supports higher prices than cost-plus suggests.
  • Volume sensitivity varies wildly. Commodity products are price-sensitive; specialized services are not. A 20% price increase on a niche service may lose 0% of clients.
  • Do not optimize purely on margin percentage. A 30% margin on $10,000 deals ($3,000 profit) beats a 60% margin on $500 deals ($300 profit) if volume is similar.
  • Test price increases on new clients first before changing existing client rates.

Frequently asked questions

What does the Pricing Optimizer AI skill do?

Analyze pricing against costs and margins to optimize profitability.

Why use Pricing Optimizer on TypingMind?

Because you install it once and use it with any model. Pricing Optimizer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pricing Optimizer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openaccountant/skills/tree/main/business/pricing-optimizer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pricing Optimizer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pricing Optimizer?

As many as you like. As long as a model supports skills, you can use Pricing Optimizer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pricing Optimizer AI skill free?

Yes. It is published on GitHub by openaccountant under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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