
X Tweets by URL
FreeScrape and normalize tweets from any X URL effortlessly.
Free · Opens the source repo
What X Tweets by URL does
X Tweets by URL is a Python-based skill designed for developers and data analysts who need to extract tweets from various types of X (formerly Twitter) URLs. This skill can handle search results, user profiles, individual tweets, and lists, providing a unified interface for scraping tweet data. It processes input URLs, determines the appropriate GraphQL endpoint, and retrieves structured tweet data, including text, author information, engagement metrics, media, hashtags, and mentions. The output is formatted for easy consumption, making it ideal for further analysis or integration into applications.
To use the skill, an active X session is required, ensuring that the user is logged in to access tweet data. The skill employs a two-step process: first, it classifies the URL to identify the type of timeline it corresponds to, and then it navigates to that endpoint to capture the tweets. The skill also supports pagination, allowing users to gather a complete set of tweets from a conversation or list by scrolling through the timeline until a specified condition is met.
This skill is particularly useful for social media analysts, researchers, and developers who need to monitor trends, collect data for sentiment analysis, or aggregate tweets from specific users or topics. By automating the scraping process, users can save time and focus on interpreting the data rather than manually collecting it.
However, it is important to note that this skill only operates within the constraints of what the user can access in their browser. It does not bypass authentication or scrape data that is not visible to the user. Therefore, users should ensure they have the necessary permissions to access the tweets they wish to scrape.
When to use it
Use this skill when you need to collect tweets from multiple X URLs for analysis or monitoring purposes.
When not to use it
This skill is not suitable for scraping data from private accounts or for users who do not have an active X session.
What you can build with it
Collecting Tweets from a User Profile
Use the skill to scrape all tweets from a specific user's profile for analysis or reporting.
Aggregating Tweets from a List
Scrape tweets from a curated list of user accounts to monitor conversations around a particular topic.
Extracting Data from Search Results
Utilize the skill to gather tweets related to specific keywords or hashtags from X search results.
How to install X Tweets by URL
View source1. Install with the skills CLI
npx skills add browser-act/skills/x-tweet-by-url --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by browser-actX — 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=$(python scripts/classify-url.py '{url}')
classify-url.py outputs a JSON object with fields:
normalized_url: the URL withtwitter.comrewritten tox.com.kind: one ofsearch,user_tweets,user_replies,user_media,tweet_detail,list,unknown.endpoint: the GraphQL endpoint name to filter by (SearchTimeline/UserTweets/UserTweetsAndReplies/UserMedia/TweetDetail/ListLatestTweetsTimeline).extract_source: the--sourcevalue to pass toparse-tweets.py(search/user_tweets/user_replies/user_media/tweet_detail/list).params: detected path parameters (handle,tweet_id,list_id) when applicable.
If kind == "unknown", report to the user that the URL is not a supported X timeline type and stop.
Step 2 — navigate and capture the first page:
network requests --clearnavigate "$(echo "$META" | python -c "import sys,json;print(json.load(sys.stdin)['normalized_url'])")"wait stable --timeout 25000(timeout is normal on X; proceed)- Let
EP=endpointfrom$META.network requests --type xhr,fetch --filter "$EP"→ take the latest entry'srequest_id. network request <request_id>→ save totmp/x-url-page-1.txt.- Let
SRC=extract_sourcefrom$META.python scripts/parse-tweets.py --json-file tmp/x-url-page-1.txt --source "$SRC".
Endpoint characteristic: URL contains /i/api/graphql/<hash>/<endpoint-name>. The query hash rotates; always filter by name.
Step 3 — paginate via scroll (skip when kind == "tweet_detail" and only the focal tweet is required; keep paginating when collecting the full reply thread):
network requests --clearscroll down --amount 5000wait stable --timeout 10000network requests --type xhr,fetch --filter "$EP"→ newest entry'srequest_idnetwork request <request_id>→ save totmp/x-url-page-N.txtpython 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 == 0on the current page.cursor_bottomis 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_name": "NASA",
"name": "NASA",
"url": "https://x.com/NASA",
"is_verified": false,
"is_blue_verified": true,
"verified_type": "Government",
"profile_picture": "https://pbs.twimg.com/profile_images/.../photo.jpg",
"description": "Explore the universe ...",
"location": "Pale Blue Dot",
"followers": 92137231,
"following": 305,
"created_at": "Wed Dec 19 20:20:32 +0000 2007"
}
}
],
"count": 20,
"cursor_top": "DAADDAABCgABHLoyRYoXoV4...",
"cursor_bottom": "DAADDAABCgABHLoyRYoXoV4..."
}
Pagination
Network Capture Pagination: triggered by scroll down. X's page JS automatically inserts the previous response's cursor_bottom into the next request's variables.cursor. Termination: count == 0, cursor_bottom 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, created_at, author.user_name, like_count, retweet_count, reply_count AND each subsequent page's cursor_bottom 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}, orhttps://x.com/i/lists/{id}are supported. Internal pages like Communities, Bookmarks, Likes, and Notifications fall back tokind: unknown. twitter.comURLs are rewritten tox.comautomatically; mobile (mobile.twitter.com) URLs are NOT rewritten and may fail — pass the canonicalx.comform.- Protected, suspended, or deleted resources return empty responses; the Skill terminates the loop and reports the cause.
view_countisnullfor very new or low-traffic tweets where X has not emittedviews.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
kindin 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_bottomand 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 byid.
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.
Frequently asked questions about X Tweets by URL
Similar skills
Mimic Dataset
Augment HDF5 recordings by replicating trajectories with noise.
Parallel Data Load
Efficiently load sharded datasets into cuPyNumeric arrays.
LaminDB
Manage and track biological datasets with ease.
TikTok Hashtag Videos
Scrape TikTok videos by hashtag with full metadata.
Douyin Video Search
Efficiently search and retrieve Douyin video data by keyword.
X Tweet Search by Query
Efficiently collect and analyze tweets using advanced queries.
