X (Twitter) — Tweet Search & Scraper
Search query / handle / URL → structured tweet list (text, author, metrics, media, entities)
Language
All process output to user (progress updates, process notifications) follows the user's language.
Objective
Collect tweets matching a search query, from specific user profiles, or from direct URLs, extracting complete structured data for each tweet.
Prerequisites
- Target page is already open in the browser:
https://x.com/search?q=...orhttps://x.com/{handle}or a direct tweet/list URL - User must be logged in to X (user avatar or username visible in left sidebar)
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 "@username" visible at the bottom → logged in, continue
- "Sign in" or "Log in" button visible → not logged in, inform user that X login is required and assist with 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 reads tweet data already rendered in the X DOM, never bypassing authentication. JS is encapsulated in
scripts/files, invoked viaeval "$(python scripts/xxx.py)". Use the bash tool for execution.
DOM: Tweet list extraction (React Fiber)
Extracts all currently visible tweets from the page via React internal state (React Fiber). Works on search pages, profile pages, list pages, and any X page rendering tweet articles.
Wait for tweets to appear before extracting:
wait --selector "article[data-testid='tweet']" --state attached --timeout 15000
Extract: eval "$(python scripts/extract-tweets.py)"
Returns a JSON array. Each element:
[
{
"id": "2059255862548738182", // tweet ID
"url": "https://x.com/NASA/status/2059255862548738182", // direct link
"text": "Full tweet text including hashtags and URLs", // full_text field
"created_at": "2026-05-26T12:50:31.000Z", // ISO 8601
"lang": "en", // ISO 639-1 language code, null if unknown
"author_id": "11348282", // author user ID
"author_name": "NASA", // display name
"author_screen_name": "NASA", // @handle (without @)
"author_profile_image": "https://pbs.twimg.com/profile_images/.../photo.jpg",
"author_followers": 92080161, // follower count
"author_following": 305, // following count
"author_verified": false, // legacy blue checkmark
"author_blue_verified": true, // X Blue / Gold / Gray checkmark
"author_location": "Washington, D.C.", // profile location, null if not set
"author_description": "Explore the universe...", // bio, null if empty
"like_count": 82579,
"retweet_count": 11952,
"reply_count": 4230,
"quote_count": 1850,
"bookmark_count": 12400,
"view_count": 25923006, // null if not available
"is_retweet": false,
"is_quote": false,
"is_reply": false,
"in_reply_to_tweet_id": null, // parent tweet ID if is_reply=true
"in_reply_to_user": null, // @handle of replied-to user
"conversation_id": "2059255862548738182",
"hashtags": ["AI", "Space"], // without #
"urls": ["https://example.com/article"], // expanded URLs from entities
"mentions": ["SpaceX", "ESA"], // @handles without @
"media": [
{
"type": "video", // "photo", "video", "animated_gif"
"url": "https://pbs.twimg.com/amplify_video_thumb/.../img/thumb.jpg",
"alt_text": null,
"video_variants": [
{"bitrate": 2176000, "url": "https://video.twimg.com/.../1280x720/video.mp4"},
{"bitrate": 832000, "url": "https://video.twimg.com/.../640x360/video.mp4"}
]
}
],
"source_name": "Twitter for iPhone", // client used to post
"source_url": "http://twitter.com/download/iphone"
}
]
URL Construction Guide
Input type → URL mapping
searchTerms (keyword / advanced query):
- Sort Latest:
https://x.com/search?q={url_encoded_query}&src=typed_query&f=live - Sort Top:
https://x.com/search?q={url_encoded_query}&src=typed_query - Sort Latest+Top: run both URLs in sequence, deduplicate by tweet ID
twitterHandles (scrape a user's profile tweets):
- Option A (profile page):
https://x.com/{handle}— shows all tweets/retweets - Option B (search): use
from:{handle}as the search query — more filter-compatible
startUrls (direct URLs): navigate to the URL as-is. Supported types:
- Tweet URL:
https://x.com/{user}/status/{id}— single tweet conversation - Profile URL:
https://x.com/{handle}— profile timeline - Search URL:
https://x.com/search?q=...— use directly - List URL:
https://x.com/i/lists/{list_id}— list timeline
Filter parameters → query operators
Append these operators to the base query string (space-separated):
| Parameter | Query operator | Example |
|---|---|---|
tweetLanguage |
lang:{code} |
lang:en |
onlyVerifiedUsers |
filter:verified |
|
onlyTwitterBlue |
filter:blue_verified |
|
onlyImage |
filter:images |
|
onlyVideo |
filter:videos |
|
onlyQuote |
filter:quote |
|
author |
from:{handle} |
from:NASA |
inReplyTo |
to:{handle} |
to:NASA |
mentioning |
@{handle} |
@NASA |
minimumRetweets |
min_retweets:{n} |
min_retweets:100 |
minimumFavorites |
min_faves:{n} |
min_faves:500 |
minimumReplies |
min_replies:{n} |
min_replies:10 |
start |
since:{YYYY-MM-DD} |
since:2024-01-01 |
end |
until:{YYYY-MM-DD} |
until:2024-06-01 |
geotaggedNear + withinRadius |
near:"{location}" within:{radius} |
near:"New York" within:15mi |
geocode |
geocode:{lat},{lon},{radius} |
geocode:40.7,-74.0,10km |
-filter:retweets |
exclude retweets |
Example: Scrape English tweets from NASA since 2024 with ≥100 likes, excluding retweets:
query = "from:NASA lang:en since:2024-01-01 min_faves:100 -filter:retweets"
url = "https://x.com/search?q=" + encodeURIComponent(query) + "&src=typed_query&f=live"
Pagination
DOM Pagination (scroll to load more):
X dynamically appends new tweet articles to the DOM as the user scrolls. Tweets already rendered remain in the DOM (no virtualization for typical result sets < ~500 tweets).
Loop pattern:
- Record current tweet count: extract → note
len(results) scroll down --amount 2000wait stable- Extract again → compare IDs, add new ones to collection
- Termination conditions:
- New extraction returns 0 new tweet IDs (end of results reached)
collected >= max_items(if limit specified)- Same tweet IDs returned 3 consecutive times (no more data loading)
Deduplication: track seen IDs in a Python set, filter before appending to output.
Success Criteria
result count >= 1 and id field non-null rate = 100% and text field non-null rate = 100%
Known Limitations
- React Fiber key: The
__reactFiberprefix includes a session-specific hash (e.g.,__reactFiber$ozawbbp0gp). The script usesstartsWith('__reactFiber')which is stable across deployments; only fails if React is replaced with a different framework. - DOM virtualization: For very large result sets (500+ tweets), X may virtualize older DOM nodes to reclaim memory. If extraction suddenly returns fewer tweets than expected after extended scrolling, the remaining tweets may have been removed from DOM. Mitigation: save results incrementally after each scroll batch.
- View count:
view_countis null for older tweets, low-engagement tweets, or when X doesn't expose it. This is a data availability issue, not an extraction failure. - List URL: Requires a valid, accessible public list ID. Private lists return no tweets.
filter:blue_verified: Whether X's search engine respects this operator may vary; verify results if blue-verified filtering is critical.customMapFunction: Not applicable — this is a source-platform-specific JS transform parameter, not a data filter relevant to browser extraction.- Rate limiting: X may temporarily stop loading new tweets after aggressive scrolling. Add 1–2s delays between scroll batches for large collections.
Execution Efficiency
- Batch orchestration: For multiple search queries or handles, process them serially in one browser session with short delays (1–2s) between navigations. Do not open parallel searches in the same browser — use separate sessions for parallel work.
- Test before batch execution: Test with 1 query first, verify 10+ tweets extract correctly, then run the full batch.
- Reduce redundant pre-operations: Login check only needed once per session; skip on subsequent queries.
- Error resumption: Save results to a file after each URL/query. On failure, resume from the last saved query rather than restarting from scratch.
- Incremental save: After each scroll batch, append new tweets to the output file rather than holding everything in memory.
Experience Notes
Path: {working-directory}/browser-act-skill-forge-memories/x-tweet-scraper-x-tweet-search.memory.md
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 keywords were used or how many results were returned — those are task outputs, not experience.