Mmcp.market

x-tweet-by-url skill

by browser-act·browser-act/skills·6.0k stars·MIT

Scrapes tweets from any X (Twitter) URL — search results, user profile, single tweet detail, or list timeline — and returns normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, and cursor for pagination. Use when user mentions X URL scraper, Twitter URL scraper, scrape from URL, given an X link, given a Twitter link, accept mixed X URLs, accept mixed Twitter URLs, search URL, profile URL, list URL, status URL, tweet detail URL, scrape startUrls Twitter, X startUrls, mixed batch of Twitter links, paste links and scrape, mass URL extraction X, mass URL extraction Twitter, scrape from a list of links, x.com URLs, twitter.com URLs, classify Twitter URLs, auto-detect Twitter URL type, scrape lists on X, scrape Twitter lists, list timeline scraper, list tweet scraper, scrape conversation by URL. Also applies to processing seed URL files, dispatching mixed X URLs through a single workflow, list-based KOL monitoring, batch-collecting tweets from a curated list of profiles, lists, and individual posts.

A97/100content scan

Is the x-tweet-by-url skill safe?

Clean: nothing in its files matched our rules. We read 3 files in the folder on 2026-09-28.

  • lowSKILL.md:1

    The description is over 1,024 characters, the limit agents read.

    1046 characters

Install the x-tweet-by-url skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/browser-act/skills.git /tmp/skills
mkdir -p ~/.claude/skills
cp -r /tmp/skills/solutions/social-listening/x-tweet-by-url ~/.claude/skills/x-tweet-by-url
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

X — Tweets by URL

Any X URL (search, profile, single tweet, list) → normalized list of tweets matching that URL's timeline.

Language

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

Objective

Accept any X URL as input, automatically detect which timeline endpoint it triggers, navigate to it, and return structured per-tweet data with pagination cursors. This unifies search, profile, single-tweet conversation, and list extraction under one entry point.

Prerequisites

  • Active X session in the browser (left sidebar shows logged-in avatar / @handle).
  • Network capture is enabled in the browser-act session.

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 X has been confirmed in the current session → skip this step.

Otherwise: open https://x.com and observe the left sidebar:

  • User avatar or @handle visible → logged in, continue
  • "Sign in" / "Log in" prompt visible → not logged in, inform the user and assist 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 tweet data already shown to the user, never bypassing authentication. The browser's own JS signs the GraphQL request; the Skill triggers it via URL navigation and reads the response from network traffic. Python scripts under scripts/ only classify URLs and parse responses — they do not call X directly. Run them through the bash tool.

Network Capture: tweets via input URL

Step 1 — classify the URL to determine which GraphQL endpoint will be triggered and which --source to pass to the parser:

META=$(python scripts/classify-url.py '{url}')

classify-url.py outputs a JSON object with fields:

  • normalized_url: the URL with twitter.com rewritten to x.com.
  • kind: one of search, usertweets, userreplies, usermedia, tweetdetail, list, unknown.
  • endpoint: the GraphQL endpoint name to filter by (SearchTimeline / UserTweets / UserTweetsAndReplies / UserMedia / TweetDetail / ListLatestTweetsTimeline).
  • extractsource: the --source value to pass to parse-tweets.py (search / usertweets / userreplies / usermedia / tweet_detail / list).
  • params: detected path parameters (handle, tweetid, listid) when applicable.

If kind == "unknown", report to the user that the URL is not a supported X timeline type and stop.

Step 2 — navigate and capture the first page:

  1. network requests --clear
  2. navigate "$(echo "$META" | python -c "import sys,json;print(json.load(sys.stdin)['normalized_url'])")"
  3. wait stable --timeout 25000 (timeout is normal on X; proceed)
  4. Let EP = endpoint from $META. network requests --type xhr,fetch --filter "$EP" → take the latest entry's request_id.
  5. network request → save to tmp/x-url-page-1.txt.
  6. Let SRC = extract_source from $META. python scripts/parse-tweets.py --json-file tmp/x-url-page-1.txt --source "$SRC".

Endpoint characteristic: URL contains /i/api/graphql//. The query hash rotates; always filter by name.

Step 3 — paginate via scroll (skip when kind == "tweet_detail" and only the focal tweet is required; keep paginating when collecting the full reply thread):

  1. network requests --clear
  2. scroll down --amount 5000
  3. wait stable --timeout 10000
  4. network requests --type xhr,fetch --filter "$EP" → newest entry's request_id
  5. network request → save to tmp/x-url-page-N.txt
  6. python scripts/parse-tweets.py --json-file tmp/x-url-page-N.txt --source "$SRC"

Repeat Step 3 until any termination condition is met:

  • Accumulated unique tweet count reaches the user's target.
  • count == 0 on the current page.
  • cursor_bottom is unchanged across two consecutive pages.

Error handling: if no matching request appears after a scroll, wait 3 s and retry once. If kind == "search" and the page shows a captcha challenge (detect via state showing an "Authorize access to your account" or "Help us keep X safe" panel), pause and ask the user. If kind == "list" and the response's data.list.tweets_timeline.timeline.instructions is empty, the list is empty or access-restricted to the owner — terminate and report.

Output example:

{
  "tweets": [
    {
      "type": "tweet",
      "id": "2068333045510291908",
      "url": "https://x.com/NASA/status/2068333045510291908",
      "twitter_url": "https://twitter.com/NASA/status/2068333045510291908",
      "text": "The official FIFA World Cup ball went to space! ...",
      "created_at": "Thu Jun 20 18:30:11 +0000 2026",
      "lang": "en",
      "source": "Twitter Web App",
      "retweet_count": 4586,
      "reply_count": 1812,
      "like_count": 24499,
      "quote_count": 240,
      "bookmark_count": 1730,
      "view_count": 2098235,
      "is_reply": false,
      "is_retweet": false,
      "is_quote": false,
      "quote_id": null,
      "quote_url": null,
      "in_reply_to_id": null,
      "in_reply_to_user": null,
      "in_reply_to_user_id": null,
      "conversation_id": "2068333045510291908",
      "hashtags": ["FIFAWorldCup"],
      "mentions": [],
      "urls": [],
      "media": [
        {"type": "photo", "url": "https://pbs.twimg.com/media/abcd.jpg", "expanded_url": "https://x.com/NASA/status/2068333045510291908/photo/1", "alt_text": null}
      ],
      "card": null,
      "place": null,
      "author": {
        "id": "11348282",
        "user_

Pagination

Network Capture Pagination: triggered by scroll down. X's page JS automatically inserts the previous response's cursorbottom into the next request's variables.cursor. Termination: count == 0, cursorbottom does not advance across two consecutive pages, or user target reached. For tweet_detail, pagination loads more replies; when only the focal tweet is required, stop after the first page.

Success Criteria

kind != "unknown" AND count >= 1 on the first page (unless the source is genuinely empty) AND every tweet has non-null id, text, createdat, author.username, likecount, retweetcount, replycount AND each subsequent page's cursorbottom differs from the previous page's until termination.

Known Limitations

  • Only X resources whose URLs match https://x.com/search, https://x.com/{handle}, https://x.com/{handle}/with_replies, https://x.com/{handle}/media, https://x.com/{handle}/status/{id}, or https://x.com/i/lists/{id} are supported. Internal pages like Communities, Bookmarks, Likes, and Notifications fall back to kind: unknown.
  • twitter.com URLs are rewritten to x.com automatically; mobile (mobile.twitter.com) URLs are NOT rewritten and may fail — pass the canonical x.com form.
  • Protected, suspended, or deleted resources return empty responses; the Skill terminates the loop and reports the cause.
  • view_count is null for very new or low-traffic tweets where X has not emitted views.count.
  • Sustained polling triggers per-session throttling; stay under ~150 timeline calls per 15-minute window per session.

Execution Efficiency

  • Batch orchestration: write a bash script that iterates URLs serially in one session; URLs of mixed kinds are fine because the classifier picks the right endpoint per URL. To parallelize, fan out across multiple stealth browsers, each with its own login and rate budget.
  • Test before batch execution: run one URL of each kind in your input set end-to-end before the full batch — different timelines have slightly different cursor advance patterns.
  • Reduce redundant pre-operations: keep the same session for many sequential URLs.
  • Error resumption: persist cursor_bottom and accumulated tweet IDs per URL after every page.
  • De-duplicate by id: when the same tweet is reachable via multiple input URLs (search + profile, profile + status), merge by id.

Experience Notes

Path: {working-directory}/browser-act-skill-forge-memories/x-tweet-scraper-x-tweet-by-url.memory.md (working directory is determined by the Agent running the Skill, typically the project root or current working directory)

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 URLs were processed or how many tweets were returned — those are task outputs, not experience.

More skills from browser-act/skills

  • A1688-product-detailExtracts 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.
  • Aairbnb-listing-detailFetches 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.
  • Aairbnb-search-listingExtracts 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.
  • Aamazon-alexa-qaAmazon 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.
  • Aamazon-asin-lookup-api-skillThis 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.
  • Aamazon-best-selling-products-finder-api-skillThis 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.
  • Aamazon-bestseller-listingAmazon 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.
  • Aamazon-buy-box-monitor-api-skillThis 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.
  • Aamazon-competitor-analyzerScrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
  • Aamazon-listing-competitor-analysis-skillThis skill helps users analyze Amazon competitor listings by ASIN and produce structured competitive intelligence plus strategic opportunity points for their own go-to-market. The Agent should proactively apply this skill when users want to analyze a competitor Amazon listing by ASIN, understand what a top-ranked product does right in content keywords or visuals, find market gaps and unmet buyer needs, turn competitor research into opportunity maps for their brand, identify keyword placement patterns on rival listings, extract SEO insights from Amazon product pages, reverse-engineer competitor bullet and title strategies, mine competitor reviews for buyer psychology, compare seller and A plus content patterns, run gap analysis before launching a new SKU, research why a listing wins conversion signals, synthesize whitespace you can own versus the diagnosed listing, or say just look at this ASIN with a competitive or optimization angle.
  • Aamazon-product-api-skillThis skill helps users extract structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications. Use this skill when users want to search for products on Amazon, find the best selling brand products, track price changes for items, get a list of categories with high ratings, compare different brand products on Amazon, extract Amazon product data for market research, look for products in a specific language or marketplace, analyze competitor pricing for keywords, find featured products for search terms, get technical specifications like material or color for product lists.
  • Aamazon-product-detailAmazon product detail page scraper: extract full product data from any open Amazon product detail URL (any /dp/{asin} or /gp/product/{asin} page across all Amazon regional TLDs) — returns asin, url, title, brand, price, listPrice, stars, reviewsCount, starsBreakdown (5/4/3/2/1 star percentages), answeredQuestions, inStock, inStockText, delivery, fastestDelivery, returnPolicy, breadCrumbs, features (bullet points), description, bookDescription, thumbnailImage, highResolutionImages, galleryThumbnails, productOverview (Brand/Model/etc.), attributes (tech spec table), attributesMapped (flat key-value), bestsellerRanks (rank + category + url), variantAttributes (currently selected color/size/style), variantAsins, seller (name + id + url), isAmazonChoice, amazonChoiceText, monthlyPurchaseVolume, hasAPlusContent, hasBrandStory, aiReviewsSummary, reviewsLink, productPageReviews (sample), videosCount, locationText, loadedCountryCode. Works on amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, amazon.com.mx, amazon.com.br, amazon.nl, amazon.se, amazon.sg, amazon.ae, amazon.sa, amazon.pl, amazon.tr, amazon.eg. Use when user mentions Amazon product page, Amazon /dp/, Amazon dp URL, Amazon ASIN scraper, Amazon product detail, Amazon PDP, Amazon product data, Amazon product info, Amazon product fields, Amazon product attributes, Amazon full field extraction, Amazon per-ASIN enrichment, Amazon rating breakdown, Amazon stars breakdown, Amazon bestseller rank, Amazon BSR, Amazon variants, Amazon variant ASINs, Amazon color size options, Amazon feature bullets, Amazon A+ content, Amazon brand story, Amazon AI review summary, Amazon bought in past month, Amazon monthly sales volume, Amazon Amazon's Choice badge, Amazon seller info, scrape Amazon product, enrich Amazon ASIN, Amazon ASIN details, Amazon product review data. Also applies to bulk ASIN enrichment from a list of URLs, competitive product research, brand catalog audits, price and stock monitoring per ASIN, and building a normalized product dataset from a list of Amazon URLs.

All agent skills → · MCP servers