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Amazon Profit Analyzer

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liangdabiao
amazon-profit-analyzer

Comprehensive Amazon profit analysis — revenue breakdown, fee structure, true net margin, and optimization opportunities. Analyzes per-ASIN and portfolio-level profitability including advertising costs, returns, and hidden fees.

Overview

Publisherliangdabiao
RepositoryAmazon-Skills-Liang
Skill nameamazon-profit-analyzer
Stars
99
Forks
20
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Amazon Profit Analyzer 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/liangdabiao/Amazon-Skills-Liang/tree/main/skills/amazon-profit-analyzer
  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/liangdabiao/Amazon-Skills-Liang.git /tmp/Amazon-Skills-Liang
mkdir -p .claude/skills
cp -r /tmp/Amazon-Skills-Liang/skills/amazon-profit-analyzer .claude/skills/amazon-profit-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amazon Profit Analyzer 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 Amazon Profit Analyzer 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 Amazon Profit Analyzer 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.

Amazon Profit Analyzer 💰

Comprehensive Amazon profit analysis — revenue breakdown, fee structure, true net margin, and optimization opportunities. Analyzes per-ASIN and portfolio-level profitability including advertising costs, returns, and hidden fees.

Supported platforms: Amazon (US, UK, DE, CA, JP, AU, and all marketplaces).

Usage

Analyze the profitability of my Amazon product: I sell a yoga mat for $34.99, COGS is $8, I spend $400/month on PPC with 15% ACoS. My return rate is about 5%. Is this product actually profitable?

Capabilities

  • Per-ASIN profit waterfall: Revenue → COGS → FBA fees → referral fees → ad spend → returns → net profit
  • Hidden fee identification: long-term storage, removal orders, reimbursement gaps, coupon costs
  • ACoS/TACoS impact on true margin — break-even ACoS calculation
  • Return cost analysis: return shipping, restocking loss, unsellable inventory
  • Portfolio-level profitability: identify top performers vs. margin drains
  • Scenario modeling: price change impact, fee increase simulation, ad budget shifts
  • Benchmark comparison: category-average margins, fee ratios, return rates

How This Skill Works

Step 1: Collect product details from the user — selling price, COGS, category, dimensions/weight (for FBA fees), monthly units, ad spend, return rate.

Step 2: Ask one follow-up with all remaining questions using multiple-choice format. Allow shorthand answers (e.g., "1b 2c 3a").

Step 3: Build a complete profit waterfall breaking down every cost line. Calculate true net margin after ALL fees (not just the obvious ones).

Step 4: Deliver structured output with specific dollar amounts, margin percentages, and prioritized optimization recommendations.

Output Format

  • Profit waterfall table: each cost as $ amount and % of revenue
  • True net margin (not gross margin — include everything)
  • Break-even analysis: minimum price, maximum ACoS, maximum return rate
  • Top 3 optimization opportunities ranked by $ impact
  • Mark estimates with ⚠️ when based on incomplete data (e.g., assumed FBA fees without exact dimensions)
  • End with concrete next steps

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Amazon Profit Analyzer AI skill do?

Comprehensive Amazon profit analysis — revenue breakdown, fee structure, true net margin, and optimization opportunities. Analyzes per-ASIN and portfolio-level profitability including advertising costs, returns, and hidden fees.

Why use Amazon Profit Analyzer on TypingMind?

Because you install it once and use it with any model. Amazon Profit Analyzer 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 Amazon Profit Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/liangdabiao/Amazon-Skills-Liang/tree/main/skills/amazon-profit-analyzer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Amazon Profit Analyzer?

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 Amazon Profit Analyzer?

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

Is the Amazon Profit Analyzer AI skill free?

It is published on GitHub by liangdabiao. Check the repository for licensing terms. 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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