search-product▌
aliexpress.com/search-product-p0h8a7 · updated May 21, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Search AliExpress by product name / keyword and return a structured list of matching listings — productId, canonical detail URL, title, current price, list price, discount %, rating, sold count, and badges. Read-only.
| name | search-product |
| title | AliExpress Search Products by Name |
| description | >- Search AliExpress by product name / keyword and return a structured list of matching listings — productId, canonical detail URL, title, current price, list price, discount %, rating, sold count, and badges. Read-only. |
| website | aliexpress.com |
| category | ecommerce |
| tags | - ecommerce - aliexpress - search - products - read-only |
| source | 'browserbase: agent-runtime 2026-05-19' |
| updated | '2026-05-19' |
| recommended_method | browser |
| alternative_methods | - method: api rationale: >- No public storefront API for search. AliExpress's internal MTOP/GraphQL endpoints (gdp.alicdn.com/mtop.aliexpress.search.*) require per-request Alibaba `sign` headers derived from browser-only `_m_h5_tk` cookies and cannot be replayed from a cookieless HTTP client. Confirmed dead-end during iteration. - method: url-param rationale: >- The canonical URL pattern (/w/wholesale-<slug>.html) takes SortType/minPrice/maxPrice/shipFromCountry filter params, but item data is server-rendered into the DOM, not exposed as JSON — a browser is still required to extract. |
| verified | true |
| proxies | true |
AliExpress Search Products by Name
Purpose
Given a product name / search query (e.g. "wireless headphones", "iphone 15 case"), return a structured list of matching AliExpress listings — for each result: product id, canonical detail-page URL, title, current price, original/list price (when discounted), discount %, star rating, sold count, and promotional badges. Read-only — never adds to cart, never proceeds to checkout, never signs in.
When to Use
- Quick product discovery: "find me {query} on AliExpress".
- Comparing the cheapest or best-rated listings for a generic product across sellers.
- Building a price/availability watcher for a query slug.
- Feeding a downstream "fetch product detail" skill — this skill returns the
productIdand canonical detail URL each item-detail skill needs.
Workflow
The recommended path is browser-driven. There is no public JSON API for the storefront search surface — items are server-side-rendered into the page's HTML, and the GraphQL/MTOP endpoints AliExpress uses internally (gdp.alicdn.com/mtop.aliexpress.*) require Alibaba-signed m-h5-tk + _m_h5_tk_enc browser cookies and a per-request sign derived from those (not reproducible from a cookieless curl). The page-rendered HTML is the cheapest reliable surface. A stealth + residential-proxy session (--verified --proxies) is required — bare sessions trip Cloudflare/Akamai-style verification challenges intermittently from datacenter IPs.
Important architectural note for the agent reading this: search-results items are NOT in window._dida_config_._init_data_ (the page-state blob). The cards2023_* field where you'd expect them is empty — items are baked directly into the rendered DOM. Don't waste turns inspecting that object.
1. Create a stealth + proxied session
sid=$(browse cloud sessions create --keep-alive --verified --proxies \
| node -e "let s='';process.stdin.on('data',c=>s+=c).on('end',()=>process.stdout.write(JSON.parse(s).id))")
export BROWSE_SESSION="$sid"
Both --verified and --proxies are required. AliExpress shows captcha / "Verify you're human" pages on a non-trivial fraction of bare-session loads.
2. Navigate to the canonical search URL
# Slugify the query: lowercase, ASCII letters/digits only, spaces → hyphens.
slug=$(echo "$QUERY" | tr '[:upper:]' '[:lower:]' | sed 's/[^a-z0-9]\+/-/g' | sed 's/^-//;s/-$//')
browse open "https://www.aliexpress.com/w/wholesale-${slug}.html" --remote
browse wait load --remote
browse wait timeout 3500 --remote # search grid hydrates 1–3 s after `load`
Equivalent URL form: https://www.aliexpress.com/wholesale?SearchText=<urlenc> — AliExpress 302-redirects this to the canonical /w/wholesale-<slug>.html path. Prefer the canonical form to skip the redirect round-trip.
Optional URL params (appended as ?key=val&...):
| Param | Meaning |
|---|---|
SortType=default | Best Match (default) |
SortType=total_tranpro_desc | Sort by Orders (most-sold first) |
SortType=price_asc / price_desc | Sort by price ascending / descending |
SortType=latest_desc | Newest listings first |
minPrice=N&maxPrice=N | Numeric price bounds in the page's currency |
shipFromCountry=US,CN,... | Filter origin country (comma-separated ISO-2) |
g=y | Filter to "Choice" (AliExpress-curated faster shipping) items |
Unrecognized params are silently dropped.
3. Extract listings from the rendered DOM
Each search result is an <a href="/item/<productId>.html"> anchor (hostname is either www.aliexpress.com or www.aliexpress.us — both resolve to the same product). The anchor's innerText is already neatly line-broken by the page's CSS — split on \n, trim, and classify each line by pattern. The DOM uses obfuscated class names (k7_kg, k7_l7, nc_nf, …) that change per build — selecting by class is brittle; rely on the line-split heuristic below instead.
// Run via: browse eval --remote --session "$sid" '(() => { ... })()'
(() => {
const seen = new Set();
const items = [];
for (const a of document.querySelectorAll('a[href*="/item/"]')) {
const m = a.href.match(/\/item\/(\d+)\.html/);
if (!m) continue;
const id = m[1];
if (seen.has(id)) continue;
seen.add(id);
const lines = (a.innerText || '').split('\n').map(s => s.trim()).filter(Boolean);
if (lines.length === 0) continue;
const item = {
productId: id,
url: a.href.split('?')[0], // strip tracking params
title: lines[0],
price: null,
listPrice: null,
discountPct: null,
rating: null,
sold: null,
badges: []
};
const prices = [];
for (let i = 1; i < lines.length; i++) {
const ln = lines[i];
if (/^\$[\d,]+(\.\d{1,2})?$/.test(ln)) { prices.push(ln); continue; }
if (/^-\d{1,2}%$/.test(ln)) { item.discountPct = ln; continue; }
if (item.rating === null && /^[1-5]\.\d$/.test(ln)) { item.rating = parseFloat(ln); continue; }
if (item.sold === null && /\bsold$/i.test(ln)) { item.sold = ln; continue; }
item.badges.push(ln);
}
item.price = prices[0] || null;
item.listPrice = prices[1] || null; // present only when discounted
// Drop "related search keyword" anchors — they have no price/sold and are not real products.
if (!item.price && !item.sold) continue;
items.push(item);
}
return items;
})()
Filter rule (critical): anchors with only a title line (no price, no sold count) are related-search keyword shortcuts AliExpress injects into the grid — they are NOT real products and clicking them runs another search. Drop them with the if (!item.price && !item.sold) continue; guard above.
4. (Optional) Load more results via infinite scroll
The grid is JS-paginated by scroll, not by ?page=N (anchor scans for a[href*="page="] return zero hits). Each scroll-to-bottom triggers an XHR that appends ~12–17 more items to the DOM.
# Each 3000-px scroll appends one batch. Loop until count stabilises or hits your cap.
for i in 1 2 3 4; do
browse mouse scroll 500 400 0 3000 --remote
browse wait timeout 2000 --remote
done
# Then re-run the extractor — it dedupes by productId via the `seen` Set.
Observed: initial render ~17 items; +17 per scroll batch; pages cap around 50–60 items per query in normal use. Don't infinite-loop — set a hard cap.
5. Release the session
browse cloud sessions update "$sid" --status REQUEST_RELEASE
Site-Specific Gotchas
--verified --proxiesis required. Bare sessions intermittently hit Cloudflare/Akamai verification screens. The combination has been stable across all tested queries.- Items are NOT in
window._dida_config_._init_data_. The page-state object exposeshierarchy, decode tables, and refine filters, butdata.data.cards2023_*(where items would logically live) is empty{}— the rendered grid is the canonical source. Don't waste turns spelunking_dida_config_for products. - No JSON storefront API for search. AliExpress's internal MTOP/GraphQL surface (
gdp.alicdn.com/mtop.aliexpress.search.*) requires per-request Alibabasignheaders derived from session cookies (_m_h5_tk,_m_h5_tk_enc). These can't be replayed from a cookielesscurland reverse-engineering the sign function is out of scope. The browser-rendered HTML is the practical surface. - Class names are obfuscated and per-build (
k7_kg,k7_l7,nc_nf, …). Don't select by class — they change. Use theinnerTextline-split heuristic ona[href*="/item/"]anchors. - No-results queries silently fall back to "anything goes". A query like
zxqzxqzxq123nonsensereturns ~5–6 unrelated products with no "0 results" banner. To detect a truly poor match, compare the query tokens against returned titles — if median title-token overlap is < 1, treat it asno_match. - Related-search anchors masquerade as products. Inside the grid, AliExpress injects keyword-shortcut anchors (e.g.
<a href="/item/.../1005002856476808.html">iphone 15 vans case</a>) that have only a title and no price/rating/sold. Filter them out by requiringprice || soldto be present. - Two product-page hostnames coexist:
www.aliexpress.comandwww.aliexpress.us. Same productId, same content, different geo/locale routing. Treat either as canonical; don't normalize one to the other without a reason. - The URL pattern is canonicalised to a hyphenated slug.
/wholesale?SearchText=wireless+headphones302s to/w/wholesale-wireless-headphones.html. Special characters (',&, accents) are dropped from the slug —iPhone 15 Pro Maxbecomesiphone-15-pro-max. Use?SearchText=…if you need to preserve weird query strings, accept the redirect. - Anchor URLs include heavy tracking params (
algo_pvid,pdp_npi,algo_exp_id,curPageLogUid,utparam-url). Always strip with.split('?')[0]for a clean canonical detail URL. The/item/<id>.htmlpath alone is sufficient to fetch the product. - Rating may be missing on cards. New listings (or those AliExpress chooses to suppress) omit the
^[1-5]\.\d$rating line entirely; the sold line may also be absent for brand-new items. Code defensively for nulls in both. - Pagination is infinite-scroll only — no
?page=N. Sorting viaSortType=and filtering viaminPrice/maxPrice/shipFromCountrywork via URL params, but page-number navigation does not exist in the URL contract. - Wait
~3.5safterwait loadbefore extracting. The grid hydrates progressively post-load; extracting immediately may miss the first batch of items. - The
BundleDealsURL is not a product page. A handful of anchors point to/ssr/<id>/BundleDeals2?productIds=...(a multi-product bundle landing page). The current extractor filters them naturally (no/item/<id>.htmlmatch), but be aware they appear in the grid.
Expected Output
{
"query": "wireless headphones",
"search_url": "https://www.aliexpress.com/w/wholesale-wireless-headphones.html",
"sort": "default",
"result_count": 18,
"items": [
{
"productId": "3256811752642309",
"url": "https://www.aliexpress.us/item/3256811752642309.html",
"title": "B36 Wireless Bluetooth 5.3 Over-Ear Headphones with ANC Noise Cancelling 8H Playtime Ergonomic Design HD Microphone Foldable",
"price": "$8.64",
"listPrice": null,
"discountPct": null,
"rating": 4.9,
"sold": "179 sold",
"badges": ["$2 off on $18", "Save $14.45"]
},
{
"productId": "3256806808326673",
"url": "https://www.aliexpress.us/item/3256806808326673.html",
"title": "Transparent Magnetic Case For iPhone 15 14 13 Pro Max For Magsafe Clear Wireless Charging Phone Cases",
"price": "$2.75",
"listPrice": "$6.91",
"discountPct": "-60%",
"rating": 4.9,
"sold": "100K+ sold",
"badges": ["$2 off on $18", "New shoppers save $4.16"]
}
]
}
Distinct outcome shapes:
// 1. Normal results (above)
{ "result_count": N, "items": [...] }
// 2. Nonsensical query — AliExpress returns unrelated fallback items, NOT a 0-results page.
// Detect via low query-token overlap with returned titles.
{
"query": "zxqzxqzxq123nonsense",
"result_count": 6,
"match_quality": "no_match",
"items": [ /* unrelated products — surface them as low-confidence or drop */ ]
}
// 3. Verification challenge (rare, on degraded sessions). Detect via page title
// "Verify yourself" / "Are you human" / Cloudflare branding. Recreate session.
{
"query": "...",
"error": "verification_challenge",
"hint": "Recreate session with --verified --proxies and retry."
}
How to use search-product on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add search-product
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches search-product from GitHub repository aliexpress.com/search-product-p0h8a7 and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate search-product. Access the skill through slash commands (e.g., /search-product) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★35 reviews- ★★★★★Diya Diallo· Dec 24, 2024
Useful defaults in search-product — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Ishan Sethi· Dec 16, 2024
Keeps context tight: search-product is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Pratham Ware· Dec 12, 2024
We added search-product from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ira Menon· Dec 4, 2024
We added search-product from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Xiao Verma· Nov 15, 2024
I recommend search-product for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Xiao Gonzalez· Nov 7, 2024
Registry listing for search-product matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Sophia Jain· Oct 26, 2024
Useful defaults in search-product — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Diya Rahman· Oct 6, 2024
Keeps context tight: search-product is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sakshi Patil· Sep 17, 2024
Solid pick for teams standardizing on skills: search-product is focused, and the summary matches what you get after install.
- ★★★★★Diya Farah· Sep 9, 2024
Solid pick for teams standardizing on skills: search-product is focused, and the summary matches what you get after install.
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