Fetch customer reviews for a Taobao or Tmall product by itemId, returning reviewer name, date, purchased variant, review text, and photo URLs. Use when user asks to get product reviews from Taobao, scrape Taobao customer feedback, extract buyer reviews by item ID, collect Tmall ratings and comments, 采集淘宝商品评价, 抓取淘宝买家评论, 获取淘宝商品评论, 天猫商品评价抓取, 按商品ID获取评价. Also applies to sentiment analysis of product reviews, building review datasets, and monitoring product rating changes.
npx skills add https://github.com/browser-act/skills --skill taobao-product-reviews
> itemId → paginated customer reviews (reviewer, date, purchased SKU, text, photos)
All process output to user (progress updates, process notifications) follows the user's language.
Navigate to a Taobao/Tmall product page, load the reviews section, and extract customer review content.
https://item.taobao.com/item.htm?id={itemId}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.
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 refuses or cannot log in → terminate execution.
> 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})". $(...) is bash syntax; it is recommended to use the bash tool for execution.
The reviews section is lazy-loaded below the main product area. Follow these steps to load and extract reviews:
navigate "https://item.taobao.com/item.htm?id={itemId}"wait stablescroll down --amount 8000
wait --selector "[class*='tabTitleItem--']" --state attached --timeout 10000scroll down --amount 8000 again and retry wait once morescreenshot to confirm page state; the product page may be rendering in a condensed mode — check Known Limitations beloweval "$(python scripts/extract-reviews.py '{itemId}')"Output example:
[
{
"username": "一笑奈何",
"date": "2026-06-03",
"purchasedSku": "轻巧白|英转中转换器【适用国内电器】适用马来西亚/新加坡等国家",
"content": "商品非常好,造工很用心!,还会再回购!",
"photos": [
"https://gw.alicdn.com/bao/uploaded/i1/O1CN015Cyg4b2FPR2YNq3PD_!!4611686018427383816-0-rate.jpg"
],
"rating": null
}
]
Notes:
purchasedSku: the specific variant the reviewer purchased (extracted from "已购:{sku}" prefix in review header)content: review text body; may be empty if reviewer submitted only photosphotos: review photo URLs; empty array if no photosrating: star rating; not always visible in current page layout (null is common)Error handling: if result count = 0 after scroll attempts, the reviews section may not have loaded in the current browser rendering environment. Try navigating to the product page fresh (navigate again) and repeating the scroll sequence. If still failing, this is a known rendering limitation — see Known Limitations below.
After extracting current page reviews:
eval "$(python scripts/next-review-page.py)"{"hasNext": true, "buttonText": "下一页"} if next page exists, or {"hasNext": false} if on last pagehasNext is true: state to find the "下一页" button index → click <index>wait stableeval "$(python scripts/extract-reviews.py '{itemId}')"[collection failed] Sort/filter options for reviews (e.g., newest, most helpful): these controls exist in the reviews section UI but require the tabs section to be loaded; their URL parameters are not exposed and must be set via UI clicks on the sort tabs within the reviews section.
DOM Pagination: Click the "下一页" button in the reviews section footer. Each page shows ~10 reviews. Termination: "下一页" button is absent or hasNext returns false.
result count >= 1 and username non-null rate = 100%
Path: {working-directory}/browser-act-skill-forge-memories/taobao-product-reviews.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.
Generates Instagram-ready product reels from any e-commerce product page URL. Scrapes product images, classifies by type, generates AI-animated clips via Higgsfield API, creates text overlays with style presets, and composes a 15-20 second reel with music. Supports model-based and product-only reels.
Use when fetching, searching, or analyzing transcripts from Lenny's Podcast, Dwarkesh Podcast, Cheeky Pint, 20VC, or A16z Podcast. Tier 2 (RSS+Groq Whisper) is the recommended approach -- fast, free, and most reliable. Also use when asked to "get transcript", "find episode", "summarize podcast", or "search podcast content". Do not use for general web scraping or non-podcast audio transcription.
Pick the right ComfyUI startup flags for VRAM, attention, caching, and speed — the full decision matrix for OOM (--novram / --cache-none / --disable-smart-memory), shared-VRAM creep on Windows (--reserve-vram N), model-switching with big text encoders (--cache-none), high-VRAM throughput (--gpu-only / --highvram), and attention-backend selection (--use-sage-attention for speed, --use-pytorch-cross-attention as the highest-quality / Z-Image-safe fallback). Also the acceleration-stack + Blackwell/RTX 5000 (sm_120) notes. Use when a graph OOMs (especially long video like LTX 2 / WAN), when the GPU spills into shared VRAM and slows to a crawl, when switching between models eats all RAM, when Z-Image produces black/garbled output under Sage, or when deciding which attention backend to launch with. Flag names verified against upstream comfy/cli_args.py — see Sources.
Bulk download images from login-protected gallery websites using an attached browser session. Use when asked to scrape, download, or save images from authenticated gallery pages, extract full-size images from thumbnails, or batch download from multi-page galleries.
| сайтмапы, переобход, ссылки, фиды, диагностика. Плюс scraping раздела Alice / Share of Voice (нет публичного API). вебмастер индексация, вебмастер запросы, вебмастер переобход, share of voice, sov, алиса, alice efficiency, конкуренты в алисе.
Scrape and download all images from a given URL. Takes a URL, extracts image URLs from the page, and downloads them. Uses python3/curl as primary method, falls back to browser automation if needed. Use when user provides a URL and wants to download images from that page.
Generate a photo-based rehab estimate for any property. Accepts photos from listing sites (Redfin/Zillow via Chrome), a local folder on your computer, or a shared Google Drive link. Use when a wholesaler needs repair cost estimates before making an offer, building a deal package, or validating their numbers. Grades property condition across 6 zones using the R.E.H.A.B.+F scoring framework and produces three-scenario rehab budgets (rental-ready, mid-range flip, full worst-case). Uses Chrome MCP for Redfin photo browsing, Perplexity for local contractor costs, and Firecrawl for finding listing URLs.
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Take browser-act/taobao-product-reviews from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.