browser-act-skill-forge
browser-act-skill-forge automatically explores websites to extract their internal APIs or DOM structures, then generates reusable Skill packages (SKILL.md plus executable Python scripts) for data extraction and automation tasks. Use it when you need a permanent, scalable solution for bulk data collection, API reverse-engineering, or site interaction that will run repeatedly, rather than a one-time manual extraction.
git clone --depth 1 https://github.com/browser-act/skills /tmp/browser-act-skill-forge && cp -r /tmp/browser-act-skill-forge/browser-act-skill-forge ~/.claude/skills/browser-act-skill-forgeSKILL.md
# browser-act-skill-forge
Built by [BrowserAct](https://www.browseract.com) — Your Personal Scraping Engineer · [GitHub](https://github.com/browser-act/skills/tree/main/browser-act-skill-forge)
Turns any website's data extraction or operation needs into Agent-callable capabilities. User describes what data to get or what action to perform on which site, this Skill automatically explores implementation paths (API endpoints first, DOM fallback when no API), then generates deploy-ready Skill packages (SKILL.md + Python scripts) after verification. Explore once, reuse forever — subsequent calls skip exploration cost, greatly improving execution reliability and efficiency.
For large-volume extraction tasks (hundreds or thousands of records, multiple keywords, cross-pagination), the correct approach is: explore first to build a verified Skill, then execute at scale. Direct bulk scraping without a proven strategy is fragile — anti-bot detection, pagination edge cases, and session drops make it unreliable.
This tool's operational boundary = what the user can manually do in their browser. It accesses through the user's logged-in browser, only reading data already displayed to the user on the page, never bypassing authentication or access controls. Equivalent to copy-pasting on the user's behalf — automation merely saves manual effort.
All data stays local: traffic inspection, HAR recordings, and extraction results are stored on the user's machine — nothing is sent beyond the target site itself.
## Language
All process output to user (plan confirmation, progress updates, process notifications) follows the user's language. Generated Skill file content follows the language of this skill.
---
```
Phase 0 (Tool Detection) → Phase 1 (Requirements Analysis & Confirmation) → [Loop: Phase 2 (Capability Exploration) → Phase 3 (Skill Generation)] → Delivery
```
---
## Phase 0 — Tool Detection
Already completed in current session → skip.
Invoke `browser-act` via Skill tool to load usage. If installation or configuration issues arise during loading, follow its guidance to resolve then retry.
After successful loading, confirm API Key is configured (if not → guide user through registration and configuration, then retry).
---
## Phase 1 — Requirements Analysis & Confirmation
### 1a. Parse Business Intent
Identify from user input:
- **Core objective**: what data to obtain / what action to complete
- **Target site**: whether a specific URL or platform name is given
- **Execution intent**: whether the user wants immediate execution (not just building a Skill for later). Includes batch/volume requirements (N records, multiple keywords) or single-use requests that imply "do it now"
- **Output directory**: defaults to `output/` under current working directory, overridden if user specifies
| Input type | Example | Handling |
|-----------|---------|----------|
| Explicit (URL + objective) | "Scrape front page articles from news.ycombinator.com" | Skip 1b, go to 1c |
| Semi-explicit (platform known, no URL) | "Help me monitor Weibo sentiment" | Run 1b research path |
| Pure objective (business intent only) | "Track competitor price changes" | Run 1b to research candidate sites |
If core objective is too vague to proceed, ask for clarification.
### 1b. Target Site Research (when no explicit URL)
Don't recommend based on model internal knowledge — actively search to find sites hosting the needed data:
1. Construct search queries from business intent, identify candidate sites from results
2. Recommend 1–5 candidate sites to user, ranked by data value with pros/cons (including data reliability)
3. After user selects, confirm target URL
### 1c. Task Decomposition & Execution Plan Confirmation
After confirming target site, first check: is there already an installed Skill for this site/capability? If yes → inform user and skip to Delivery step 4 (batch execution).
If no existing Skill, complete decomposition and **confirm all information with user at once** — no per-capability follow-up questions afterward:
1. Identify independent stages involved (search, list page, detail page, login, submission…)
2. Determine type: **extraction** (get data) vs **operation** (perform action)
3. Splitting criteria: **If you swap the business objective, can this stage be reused independently? Yes = independent capability.** Cross-page steps serving the same business objective (e.g., list page collection + detail page extraction) stay as one capability, orchestrated via composite components
4. Set `skill-name` and capability directory names (lowercase English, hyphen-separated), create directories under `output/{skill-name}/` (use user-specified path if given)
5. Confirm complete execution plan with user:
```
Target site: {url}
Output: output/{skill-name}/
Capabilities (executed in order):
1. {site-slug}-{capability-slug} ({extraction/operation}) — {one-line description}
2. {site-slug}-{capability-slug} ({extraction/operation}) — {one-line description}
...
```
If execution intent was identified in 1a, append to the plan:
```
Pipeline:
1. Explore site → discover and verify viable API endpoints or DOM extraction methods
2. Generate Skill files (SKILL.md + scripts)
3. Automated testing to confirm Skill works
4. Install Skill
5. Read installed Skill → write and run batch scripts to fulfill user's original task
```
Present the plan and wait for user to confirm or adjust. Do not ask separate questions about items that have reasonable defaults (output directory, naming conventions, etc.).
After user confirms, enter execution loop with no mid-process questions.
---
> **Phase 2 and Phase 3 below execute in a loop for each capability unit — complete one before starting the next.**
---
## Phase 2 — Capability Exploration
Read the corresponding reference file based on capability type:
- **Extraction** → `references/exploration_extraction.md`
- **Operation** → `references/exploration_operation.md`
**Goal**: prioritize AExtracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 1688 shop score, DSR score 1688, 1688 buyer protection, 1688 cross-border, 1688 dropship. Also applies to: scraping bulk product data from 1688 by offer ID list, monitoring 1688 supplier metrics, extracting 1688 pricing tiers for resale analysis.
Fetches complete Airbnb listing details for a given numeric listing ID via the internal GraphQL API, returning title, room type, description, amenities, photos, coordinates, city, house rules, highlights, ratings, review count, bedroom configuration, and property overview. Use when user mentions Airbnb listing details, Airbnb property info, Airbnb room details, get Airbnb listing data, Airbnb amenities list, Airbnb house rules, Airbnb property description, Airbnb detail page scraper, Airbnb rooms detail, Airbnb property page data, Airbnb listing info, fetch Airbnb room details, pull Airbnb 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 for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.
Amazon Alexa for Shopping Q&A automation: submits questions to Amazon's Alexa/Rufus AI shopping assistant and collects response text; supports optional keyword search context (navigate to search results page before asking for category-specific answers). Use when user mentions Amazon Alexa, Rufus, Amazon shopping assistant, Amazon AI chat, ask Amazon, Amazon Q&A, automate Alexa questions, Rufus chatbot, Amazon assistant automation, collect Alexa responses, bulk question submission to Amazon, keyword search context, category research. Also applies to extracting Amazon product recommendations from conversational AI, automating repeated queries to Amazon's AI shopping feature, collecting Alexa shopping responses at scale, or market research within a specific product category.
This skill helps users extract structured product details from Amazon using a specific ASIN (Amazon Standard Identification Number). Use this skill when the user asks to get Amazon product details by ASIN, lookup Amazon product title and price using ASIN, extract Amazon product ratings and reviews count for a specific ASIN, check Amazon product availability and current price, get Amazon product description and features via ASIN, enrich product catalog with Amazon data using ASIN, monitor Amazon product price changes for specific ASINs, retrieve Amazon product brand and material information, fetch Amazon product images and specifications by ASIN, validate Amazon ASIN and get product metadata.
This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.
Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and pagination state (currentPage, hasNextPage, nextPageUrl). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, etc.). Use when user mentions Amazon Best Sellers, Amazon bestsellers, Amazon top 100, Amazon zgbs, Amazon /zgbs/, Amazon /gp/bestsellers/, Amazon Best Sellers Rank, Amazon BSR, Amazon top ranked products, Amazon top-selling products, Amazon chart, Amazon category ranking, Amazon best sellers by category, Amazon best sellers electronics, Amazon best sellers kitchen, Amazon best sellers toys, scrape Amazon bestsellers, extract Amazon top 100, Amazon rank scraper, Amazon best seller list, Amazon leaderboard, Amazon trending products, discover trending Amazon products, Amazon niche discovery, Amazon top ranked ASINs. Also applies to competitive intelligence via ranking snapshots, spotting up-and-coming products, sourcing bestseller ASINs for further enrichment, tracking rank changes over time, and building bestseller-per-category datasets.
This skill helps users extract basic product details other sellers prices and seller ratings from Amazon via ASIN automatically using the BrowserAct API. Agent should proactively apply this skill when users express needs like query Amazon buy box information, monitor Amazon product prices, extract Amazon product details by ASIN, check other sellers prices on Amazon, get Amazon seller ratings and feedback count, monitor buy box ownership for a specific ASIN, track Amazon fulfillment methods for competitors, compare Amazon product prices across different sellers, retrieve Amazon buy box availability status, analyze Amazon seller profile details.