amazon-bestseller-listing

Mechanism

When It Triggers · How It Works · What It Produces

Breaks down how the skill works and what it produces, so you can quickly judge whether it fits your scenario and value.

Trigger Timing

When the user provides any Amazon Best Sellers URL (/zgbs/ or /gp/bestsellers/) and wants the ranked product list, category metadata, or pagination state for competitive intelligence, niche discovery, or trend spotting.

Working Mechanism

Confirm browser-act session is available; navigate to the bestseller URL and wait for stable render
Run browser-act --session {name} eval "$(python scripts/extract-bestseller.py)" to extract #gridItemRoot cards (rank, asin, title, price, stars, etc.) plus category and pagination info
Follow nextPageUrl with ?pg=N to iterate pages up to Amazon's top-100 cap
Persist per-category JSON for crash resumption; read memory file for past quirks before run

Output Result

A structured JSON with ranked items (position, ASIN, title, price, rating), category metadata, and pagination state — ready for bestseller datasets, rank tracking, and downstream ASIN enrichment.

Use Cases

Two Typical Use Cases

Scenario 01

Seller discovers niche via kitchen bestsellers

An e-commerce seller wants to launch a new product in Amazon's kitchen category. They paste the kitchen bestsellers URL into the skill, which extracts the top-50 ranked ASINs with prices and ratings. By analyzing the list, they spot gaps where demand is high but competition is low, and source winning ASINs for deeper enrichment via other Amazon skills. This saves hours of manual browsing and informs a data-driven launch strategy.

Scenario 02

Analyst tracks cross-region rank history

A market analyst tracks monthly rank changes of electronics bestsellers across amazon.de and amazon.com. Using the skill's pagination, they snapshot top-100 items per region each month and persist JSON. Over time they build a rank history showing which products are rising or declining, enabling competitive intelligence reports for stakeholders without manual chart reading.

Skill Relationships

Which Skills I Use · Which Skills Use Me

Dependency relationships read as "the upper tier points to the lower tier." The current Skill sits in the middle tier — above are Skills that depend on it, below are Skills it depends on.

Tier 1 · These Skills Use Me

No explicit dependency

Tier 2 · Current Skill

amazon-bestseller-listingWorkflow

Tier 3 · I Use These Skills

browser-act-skill-forgeWorkflow

Full Relationship Graph

Browse this skill's relationships within its skillset. Click a node to switch the side panel; use the search box to jump to any skill.

Skill File

SKILL.md

Open in GitHub ↗

SKILL.mdLoading from GitHub…

Skill Composition

Open in GitHub ↗

SKILL.md50.0%
scripts50.0%

▸skills/amazon-bestseller-listing/
▸root
- ·SKILL.md
- ▸scripts
  - ·extract-bestseller.py

Per the Agent Skills spec, SKILL.md is the only required file. The colored bars classify the rest into the three spec-aligned optional directories (scripts / references / assets) and an 'other' bucket. The full directory tree is below.

Related in Skillset

You May Also Need These Skills

amazon-asin-lookup-api-skill

Extracts structured Amazon product details via ASIN using BrowserAct API and a Python script. Method: configure API key, run script with ASIN, monitor logs, auto-retry on failure. Outputs title, price, ratings, brand, specs, URL — enabling catalog enrichment, price tracking, and market research without manual scraping.

Workflow

amazon-product-api-skill

Extracts structured Amazon product listings (titles, ASINs, prices, ratings, specs) via BrowserAct API and a Python script. Method: configure keyword/brand/language params and run one CLI command. Value: hallucination-free, captcha-free market research, price tracking, and catalog enrichment from Amazon search results.

Cli Manual · Workflow

airbnb-search-listing

Extracts Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info. Uses a Python script to parse niobeClientData and supports cursor-based pagination. Value: enables bulk collection of Airbnb rental listings for market research and price monitoring.

Workflow

airbnb-listing-detail

Fetches full Airbnb listing details via internal GraphQL API using a numeric ID. Method: run a Python script that calls the public endpoint through browser fetch. Output: title, amenities, photos, rules, ratings, location — for property research and data enrichment without login.

Cli Manual

/amazon-bestseller-listing

When It Triggers · How It Works · What It Produces

Trigger Timing

Working Mechanism

Output Result

Two Typical Use Cases

Seller discovers niche via kitchen bestsellers

Analyst tracks cross-region rank history

Which Skills I Use · Which Skills Use Me

Full Relationship Graph

SKILL.md

Skill Composition

You May Also Need These Skills

amazon-asin-lookup-api-skill

amazon-product-api-skill

airbnb-search-listing

airbnb-listing-detail

When It Triggers · How It Works · What It Produces

Trigger Timing

Working Mechanism

Output Result

Two Typical Use Cases

Seller discovers niche via kitchen bestsellers

Analyst tracks cross-region rank history

Which Skills I Use · Which Skills Use Me

Full Relationship Graph

SKILL.md

Skill Composition

You May Also Need These Skills

amazon-asin-lookup-api-skill

amazon-product-api-skill

airbnb-search-listing

airbnb-listing-detail