Taobao Keyword Search logo

Taobao Keyword Search

OrganizationPopular
browser-act
taobao-keyword-search

Search Taobao and Tmall product listings by keyword, returning paginated product cards with title, price, shop, image, sales, and tags. Use when user asks to search Taobao, find products on Taobao/Tmall, scrape Taobao search results, get product listings from Taobao, collect Taobao items by keyword, 搜索淘宝, 淘宝关键词搜索, 采集淘宝商品, 抓取淘宝搜索结果, 淘宝天猫商品列表. Also applies to bulk keyword searches, price monitoring across keywords, and competitive product research on Taobao.

Overview

Publisherbrowser-act
Repositoryskills
Skill nametaobao-keyword-search
Stars
5.9K
Forks
295
Bundled files
1
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.

  • 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 browser-act on GitHub. Read the source before you install it.

Installation

Install the Taobao Keyword Search 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/browser-act/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/solutions/ecommerce/taobao-keyword-search .claude/skills/taobao-keyword-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Taobao Keyword Search 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 Taobao Keyword Search 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 Taobao Keyword Search 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.

Taobao — Keyword Search

keyword + optional filters → paginated product listing (itemId, title, price, shop, image, sales)

Language

All process output to user (progress updates, process notifications) follows the user's language.

Objective

Search Taobao/Tmall for products by keyword and extract product cards from search results pages.

Prerequisites

  • Target page is already open in the browser: https://s.taobao.com/search
  • User is logged in to Taobao (user avatar or nickname visible in the page header)

Pre-execution Checks

1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

2. Login Verification

If login status for Taobao has been confirmed in the current session → skip this step.

Otherwise: open https://www.taobao.com and observe the page header:

  • User nickname visible (e.g., "心林vs妞妞") → logged in, continue execution
  • "亲,请登录" or login button visible → not logged in, inform the user that Taobao login is needed first, assist the user in completing the login flow

User refuses or cannot log in → terminate execution.

Capability Components

This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. JS code is encapsulated in Python files under the scripts/ directory, invoked via eval "$(python scripts/xxx.py {params})". $(...) is bash syntax; it is recommended to use the bash tool for execution.

DOM: product search results (data extraction)

Navigate to search results URL, then extract:

  1. navigate "https://s.taobao.com/search?q={keyword}&page={page}&ie=utf8"
  2. wait stable
  3. eval "$(python scripts/search-products.py '{keyword}' --page {page} --sort '{sort}' --tab '{tab}' --start-price {startPrice} --end-price {endPrice})"

URL Parameters:

  • q: URL-encoded keyword
  • page: page number, 1-based, default 1
  • sort: sort order — empty string (default/recommended), sale-desc (by sales), price-asc (price low→high), price-desc (price high→low)
  • tab: mall for Tmall-only results; omit for all results
  • startPrice / endPrice: price range filter in yuan (e.g., startPrice=100&endPrice=500)

Output example:

json
[
  {
    "itemId": "694593508978",
    "itemUrl": "https://item.taobao.com/item.htm?id=694593508978",
    "title": "蓝牙耳机2025新款官方",
    "subTitle": "AI耳机热卖榜第1名",
    "priceYuan": 79.9,
    "priceDesc": "券后价",
    "imageUrl": "https://img.alicdn.com/imgextra/...",
    "salesCount": "40万+人付款",
    "shopName": "金运旗舰店",
    "location": "广东",
    "rating": null,
    "tags": ["政府补贴15%", "官方立减26元"]
  }
]

Notes:

  • priceYuan is the displayed price (may be post-coupon price, not pre-coupon)
  • priceDesc indicates price type: 券后价 (after coupon), 补贴价 (subsidized price), etc.
  • rating is rarely shown on search cards; null is expected
  • Sponsored/ad items have itemUrl pointing to click.simba.taobao.com — they will have itemId extracted from query params

Enum Parameters

[collection failed] sort values: confirmed values are empty string (default), sale-desc, price-asc, price-desc; no API for enumeration, values are hardcoded constants.

Pagination

URL Pagination: URL pattern https://s.taobao.com/search?q={keyword}&page={N}&ie=utf8, increment page from 1. Each page returns ~47 items. Termination: when result count < 10 or returned items duplicate previous page.

Success Criteria

result count >= 1 and itemId non-null rate = 100%

Known Limitations

  • Requires Taobao login; unauthenticated sessions redirect to login page
  • Prices shown are displayed prices (may be post-coupon), not pre-discount prices
  • Sponsored/ad items appear at unpredictable positions in results
  • Price filter (startPrice/endPrice) filters on pre-coupon prices, so post-coupon prices displayed may fall outside the requested range near boundaries
  • Taobao may return different result counts across pages; page count is approximate

Execution Efficiency

  • Batch orchestration: Write a bash script to loop through keywords serially within a single session; do not parallelize within one browser (prone to triggering anti-scraping restrictions). Add 2–3 second intervals between page navigations. To increase throughput, open multiple stealth browser sessions and distribute keywords across them.
  • Test before batch execution: After writing a batch script, you must first test with 1–2 keywords to verify the script runs correctly; only then run the full batch. Never skip testing and execute in batch directly.
  • Reduce redundant pre-operations: When scraping multiple pages for one keyword, navigate page 2, 3 etc. within the same session without re-login checks.
  • Error resumption: Save results item by item during batch processing; on failure, resume from the breakpoint rather than starting over.

Experience Notes

Path: {working-directory}/browser-act-skill-forge-memories/taobao-keyword-search.memory.md

Before execution: If the file exists, read it first — it records unexpected situations encountered during past executions (e.g., a strategy has become ineffective); adjust strategy order accordingly.

After execution: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line: {YYYY-MM-DD}: {what happened} → {conclusion}

Normal execution does not write to the file. Do not record what keywords were used or how many results were returned — those are task outputs, not experience.

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 Taobao Keyword Search AI skill do?

Search Taobao and Tmall product listings by keyword, returning paginated product cards with title, price, shop, image, sales, and tags. Use when user asks to search Taobao, find products on Taobao/Tmall, scrape Taobao search results, get product listings from Taobao, collect Taobao items by keyword, 搜索淘宝, 淘宝关键词搜索, 采集淘宝商品, 抓取淘宝搜索结果, 淘宝天猫商品列表. Also applies to bulk keyword searches, price monitoring across keywords, and competitive product research on Taobao.

Why use Taobao Keyword Search on TypingMind?

Because you install it once and use it with any model. Taobao Keyword Search 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 Taobao Keyword Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/browser-act/skills/tree/main/solutions/ecommerce/taobao-keyword-search. 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 Taobao Keyword Search?

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 Taobao Keyword Search?

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

Is the Taobao Keyword Search AI skill free?

Yes. It is published on GitHub by browser-act 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇