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vellum-ai
amazon

Shop on Amazon and Amazon Fresh through your browser

Overview

Publishervellum-ai
Repositoryvellum-assistant
Skill nameamazon
Stars
1.3K
Forks
186
Bundled files
10
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.

  • 10 bundled files

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

  • Open source

    Published by vellum-ai on GitHub. Read the source before you install it.

Installation

Install the Amazon 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.
  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/vellum-ai/vellum-assistant.git /tmp/vellum-assistant
mkdir -p .claude/skills
cp -r /tmp/vellum-assistant/skills/amazon .claude/skills/amazon
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Amazon 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 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 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.

Use browser automation for all Amazon actions. All browser operations are executed through the assistant browser CLI, invoked via host_bash. Use helper scripts with host_bash to normalize extraction results and decide the next step.

Required tools

  • host_bash for assistant browser CLI commands and deterministic helper scripts under scripts/.

Hard constraints

  • Do not call assistant browser chrome relay.
  • Do not use legacy relay-backed scripts.
  • Always require explicit user confirmation before final order submission.

Step graph (state machine)

Step 1: Classify workflow state

Run this early in each turn when intent is unclear:

bash
bun {baseDir}/scripts/amazon-intent.ts --request "<latest user request>" --checkout-reviewed <true|false> --has-cart-items <true|false>

Use the returned step to route to one of: search, variant_select, cart_review, checkout_review, fresh_slot, place_order.

Step 2: Product discovery (search)

  1. Navigate to search results page:
bash
assistant browser --session amazon navigate --url "https://www.amazon.com/s?k=<urlencoded query>"
  1. Capture current state:
bash
assistant browser --session amazon --json snapshot
assistant browser --session amazon --json extract --include-links
  1. Parse candidates deterministically:
bash
bun {baseDir}/scripts/amazon-parse-search.ts --query "<query>" --input-json '<json payload with extracted text/links>'
  1. Present top options with title, price, ASIN (if present), Prime/Fresh hints.

Step 3: Product detail + variant resolution (variant_select)

  1. Open product result.
  2. Re-snapshot + re-extract.
  3. Parse product details:
bash
bun {baseDir}/scripts/amazon-parse-product.ts --input-json '<json payload with extracted text/links>'
  1. If variation hints are present, resolve user choice before add-to-cart.

Step 4: Add to cart + verify (cart_review)

  1. Click Add to Cart on product page.
  2. Navigate to cart page and extract:
bash
assistant browser --session amazon navigate --url "https://www.amazon.com/gp/cart/view.html"
assistant browser --session amazon --json snapshot
assistant browser --session amazon --json extract --include-links
  1. Parse cart summary:
bash
bun {baseDir}/scripts/amazon-parse-cart.ts --input-json '<json payload with extracted text>'
  1. Show parsed line items and totals. Ask user to confirm cart contents.

Step 5: Fresh slot validation (fresh_slot)

For Amazon Fresh flows, explicitly verify slot selection in UI before checkout:

  1. Navigate to Fresh delivery slot surface if needed.
  2. Snapshot + extract delivery slot details.
  3. Confirm selected slot text is visible before proceeding.

If slot cannot be verified after retries, stop and ask user to choose slot manually.

Step 6: Checkout sanity (checkout_review)

  1. Navigate to checkout review page.
  2. Snapshot, extract, and capture a full-page screenshot:
bash
assistant browser --session amazon --json snapshot
assistant browser --session amazon --json extract
assistant browser --session amazon screenshot --full-page --output /tmp/amazon-checkout.jpg
  1. Validate readiness:
bash
bun {baseDir}/scripts/amazon-checkout-sanity.ts --cart-confirmed true --input-json '<json payload with extracted text>'
  1. Report missing markers (shipping/payment/total/submit action) before any submission.

Step 7: Final submit gate (place_order)

Immediately before clicking final submit button:

  1. Ask for explicit final confirmation in plain language.
  2. If user confirms, click final submit action (Place your order, Buy now, or equivalent).
  3. Take post-submit snapshot/screenshot and report confirmation details.

Retry and fallback policy

  • Retry budget: 3 attempts per step that mutates page state.
  • After each mutation, run a fresh assistant browser --session amazon --json snapshot before the next click/type.
  • If a step fails 3 times, stop and ask user to complete that step manually, then resume.

Example helper payload shape

json
{
  "phase": "search",
  "context": { "checkoutReviewed": false, "hasCartItems": false },
  "extracted": {
    "text": "...",
    "links": ["https://www.amazon.com/dp/B08XGDN3TZ"]
  },
  "userIntent": "order aa batteries"
}

Safety rules

  • Always show price/totals before confirmation.
  • Never infer final consent from prior messages; ask again right before submission.
  • If CAPTCHA or anti-bot challenge appears, ask user to solve it and continue after refresh.

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 AI skill do?

Shop on Amazon and Amazon Fresh through your browser

Why use Amazon on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vellum-ai/vellum-assistant/tree/main/skills/amazon. 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?

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?

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

Is the Amazon AI skill free?

Yes. It is published on GitHub by vellum-ai 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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