Agent skill

Amazon

by vellum-ai in vellum-ai/vellum-assistant

Shop on Amazon and Amazon Fresh through your browser. An agent skill from vellum-ai/vellum-assistant.

MITAuto-check passed

Install Amazon

skills CLI
$ npx skills add vellum-ai/vellum-assistant --skill amazon -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install vellum-ai/vellum-assistant amazon --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/amazon .claude/skills/amazon && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
amazon
GitHub stars
1.4k
Token cost
~1.2k tokens
SKILL.md length
422 words
Files
18 (incl. scripts, assets)
Skills in repo
108
Repo updated
First seen
Licence
MIT

At a glance

Shop on Amazon and Amazon Fresh through your browser. An agent skill from vellum-ai/vellum-assistant.

  • Works in 7 steps: Classify workflow state → Product discovery (search) → Product detail + variant resolution… → …
  • SKILL.md covers Required tools, Hard constraints, Step graph (state machine) and Retry and fallback policy, plus 2 more sections
  • Runs TypeScript scripts from its folder; calls bun; reaches amazon.com

What it does

Amazon is an agent skill from vellum-ai/vellum-assistant. Shop on Amazon and Amazon Fresh through your browser

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 21 other files, including scripts and assets (for example `README.md`, `scripts/__tests__/amazon-checkout-sanity.test.ts` and `scripts/__tests__/amazon-intent.test.ts`). Compatibility notes: Designed for Vellum personal assistants

It works with Bash. The repository describes itself as: An AI Assistant that’s easy to setup, does your work 24/7, knows your preferences and gets better over time. The licence is MIT.

Example prompts

  • “/amazon”

Requirements

  • Node.js
  • Compatibility (from SKILL.md): Designed for Vellum personal assistants

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Classify workflow state
  2. Product discovery (search)
  3. Product detail + variant resolution (variant_select)
  4. Add to cart + verify (cart_review)
  5. Fresh slot validation (fresh_slot)
  6. Checkout sanity (checkout_review)
  7. Final submit gate (place_order)

What it can do on your machine

Read from SKILL.md and the folder at commit c92ead1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 14 files in scripts/ (TypeScript, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • bun

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • amazon.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Vellum personal assistants

    From compatibility in the SKILL.md frontmatter.

Context cost

Amazon loads about 1.2k tokens when it runs. Until then it costs about 15 tokens; SKILL.md has 422 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~15
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from vellum-ai/vellum-assistant at commit c92ead1, republished under its MIT licence (© vellum-ai). 422 words, ~1,212 tokens.

Download SKILL.mdSave it as .claude/skills/amazon/SKILL.md (or your agent's skills folder). This skill also uses 17 other files; get the full folder from GitHub.
name
amazon
description
Shop on Amazon and Amazon Fresh through your browser
compatibility
Designed for Vellum personal assistants
metadata.icon
assets/icon.svg
metadata.emoji
🛒

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.

  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.

Show full SKILL.md (160 more words)Show less
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.

© vellum-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 17 other files (scripts, assets) in skills/amazon of vellum-ai/vellum-assistant.

  • SKILL.md
  • README.md
  • assets/icon.svg
  • scripts/__fixtures__/cart-sample.txt
  • scripts/__fixtures__/product-sample.txt
  • scripts/__fixtures__/search-sample.txt
  • scripts/__tests__/amazon-checkout-sanity.test.ts
  • scripts/__tests__/amazon-intent.test.ts
  • scripts/__tests__/amazon-parse-cart.test.ts
  • scripts/__tests__/amazon-parse-product.test.ts
  • scripts/__tests__/amazon-parse-search.test.ts
  • scripts/amazon-checkout-sanity.ts
  • scripts/amazon-intent.ts
  • scripts/amazon-parse-cart.ts
  • scripts/amazon-parse-product.ts
  • scripts/amazon-parse-search.ts
  • scripts/lib
  • … and 1 more

Open the folder on GitHubat commit c92ead1

Compare with similar skills

Amazon next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Amazon compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Amazon this skillvellum-ai/vellum-assistant1.4k—~1.2kAutomated safety check: PassMIT
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k11 repos~4.1kAutomated safety check: NotesApache-2.0
Plugin Settings Patternanthropics/claude-plugins-official38k7 repos~3kAutomated safety check: PassApache-2.0
Mole Bug Patternstw93/Mole70k—~2kAutomated safety check: PassGPL-3.0
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
E2Ecallstack/react-native-pager-view3.4k1 repos~2.1kAutomated safety check: PassMIT

Similar skills

  • Hook Development for Claude Code Plugins

    anthropics/claude-plugins-official

    Official

    Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.

    38k GitHub starsUsed in 11 repos~4.1k tokens
    Agent WorkflowsAuto-check: notes
  • Plugin Settings Pattern

    anthropics/claude-plugins-official

    Official

    Shows how Claude Code plugins keep per-project settings and state in .claude/plugin-name.local.md files with YAML frontmatter and a markdown body.

    38k GitHub starsUsed in 7 repos~3k tokens
    Agent WorkflowsAuto-check passed
  • A catalog of recurring bug shapes in the Mole Mac cleaner, used to review safety-sensitive diffs for deletion safety, unbounded commands, shell traps and weak tests.

    70k GitHub stars~2k tokensUpdated today
    DevelopmentAuto-check passed
  • Neat-Freak Knowledge Closeout

    KKKKhazix/khazix-skills

    Brings project docs, agent rule files, authorized memory and leftover workspace files back in line with what the code and runtime actually do at the end of a work session.

    21k GitHub stars~1.9k tokensUpdated 7 days ago
    Agent WorkflowsAuto-check passed
  • E2E

    callstack/react-native-pager-view

    Agentic end-to-end tests with e2e, the e2e runner. An agent skill from callstack/react-native-pager-view.

    3.4k GitHub starsUsed in 1 repo~2.1k tokens
    Testing & QAAuto-check passed
  • Runs a spec-driven workflow from PRD to epic to GitHub issues to parallel agents, with status, standup and blocked-work reports from bundled scripts.

    8.4k GitHub stars~1.1k tokensUpdated 6 mo ago
    Product & Project ManagementAuto-check passed

More from vellum-ai/vellum-assistant

All 108 skills in this repo
  • Vellum GitHub App Setup

    vellum-ai/vellum-assistant

    Create and configure a GitHub App so the assistant can push commits, open PRs, and comment under its own bot identity.

    1.4k GitHub stars~3.1k tokensUpdated today
    Auto-check passed
  • Discord App Setup

    vellum-ai/vellum-assistant

    Connect a Discord bot to the assistant via the Discord Gateway with guided application creation and intent configuration

    1.4k GitHub stars~4.2k tokensUpdated today
    Auto-check passed
  • Sentry App Setup

    vellum-ai/vellum-assistant

    Create and configure a Sentry internal integration so the assistant can manage issues, alerts, and releases under its own identity

    1.4k GitHub stars~1.3k tokensUpdated today
    Auto-check passed
  • Memory Corpus Ingest

    vellum-ai/vellum-assistant

    Ingest a large dataset into memory as a skimmed map. An agent skill from vellum-ai/vellum-assistant.

    1.4k GitHub stars~3k tokensUpdated today
    Auto-check: notes
  • Plugin Builder

    vellum-ai/vellum-assistant

    A skill your agent uses when the user wants to build, scaffold, ship, or edit a Vellum plugin that bundles multiple surfaces (hooks, tools, skills, and more) into one installable package.

    1.4k GitHub stars~3.1k tokensUpdated today
    Auto-check passed
  • Slack App Setup

    vellum-ai/vellum-assistant

    Connect a Slack app to the Vellum Assistant via Socket Mode.

    1.4k GitHub stars~2.5k tokensUpdated today
    Auto-check: warnings

Works with

Questions about Amazon

What does Amazon do?

Shop on Amazon and Amazon Fresh through your browser. An agent skill from vellum-ai/vellum-assistant. Amazon is an agent skill from vellum-ai/vellum-assistant.

How do I install Amazon in Claude Code?

Run `npx skills add vellum-ai/vellum-assistant --skill amazon -a claude-code`. Or copy the skill folder (skills/amazon in vellum-ai/vellum-assistant) into .claude/skills/amazon in your project. Claude Code loads it when a task matches its description.

How do I install Amazon in Codex?

Run `npx skills add vellum-ai/vellum-assistant --skill amazon -a codex`. Or copy the skill folder (skills/amazon in vellum-ai/vellum-assistant) into .agents/skills/amazon in your project. Codex loads it when a task matches its description.

Can I use Amazon in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vellum-ai/vellum-assistant --skill amazon -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/amazon, .gemini/skills/amazon, .github/skills/amazon and .opencode/skills/amazon in your project.

What does Amazon need to run?

Going by SKILL.md and its folder, Amazon needs TypeScript for the scripts in its folder and the command-line tools its instructions call (bun). Our summary lists: Node.js. Compatibility (from SKILL.md): Designed for Vellum personal assistants.

Does Amazon access the network?

SKILL.md names 1 domain. In commands or code: amazon.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Amazon safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Amazon use?

Amazon is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Amazon use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Amazon?

Skills that share tags, products or a category with Amazon: Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Plugin Settings Pattern (anthropics/claude-plugins-official, 38k stars), Mole Bug Patterns (tw93/Mole, 70k stars) and Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Amazon?

vellum-ai (a GitHub organization) maintains it in vellum-ai/vellum-assistant, which has 1,397 GitHub stars. The repository holds 108 skills in this directory. The repository was last updated on October 7, 2026.

Source: vellum-ai/vellum-assistant on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.