User › Tweets
Returns an account's most recent tweets in descending order, with full text, like, retweet, reply, bookmark and view counts, media, and creation time. Around 20 tweets per page.
Use it to read a timeline: pages come newest first, retweets and self-threads included, and you can page deeper by sending pagination.next_cursor back as cursor.
Metered: 20–100 credits. We reserve the ceiling when the call starts and charge what it actually used when it finishes.
Re-running the exact same call within 6h is free.
Paginates by cursor — see Pagination.
Authorization
apiKey Your key from the dashboard. It starts with isk_.
In: header
Query Parameters
Twitter username without the @ symbol
Only tweets published on or after this date: YYYY-MM-DD (midnight UTC) or an ISO 8601 timestamp. Older tweets are left off the page, and the page that reaches one ends the walk: next_cursor is not returned and pagination.stopped_at is since. Pinned tweets sit out of date order and never end the walk. The page still costs what a page costs, so a daily poll pays for the pages it walks and no more.
The id (post.id) or URL (post.url) of the newest tweet you already hold. The page stops just before it: that tweet and everything after it are left off, next_cursor is not returned, and pagination.stopped_at is known_id. A pinned tweet never counts as the stop point. If it is not on this page the page is returned in full with its cursor, so keep walking. pagination.stopped_at is end when the list ran out first and null while there is more to walk.
Accepted for backwards compatibility and ignored. It shrank the raw payload, which the canonical response never exposed, so it changed nothing you can see
Cursor from the previous response's pagination.next_cursor to fetch the next page
Optional CSV of labels to add to every post. Without this param every page already carries sponsored, intent and niche, free; label= adds the labels you name to them (the defaults keep running). judgments=off (or label=none) turns the default labels off. sponsored: is the post a paid or gifted promotion (p, 0 to 1), did it carry a disclosure marker such as #ad or 광고 (disclosed), is it likely paid with no marker (undisclosed), and which of the accounts it mentions does it promote (brand, or null). These are signals to review, never a finding. mention (needs brand=): is the post about that brand rather than something that shares its name (about_brand, 0 to 1), how it feels about the brand on five levels (sentiment_level 0 to 4 and sentiment_score 0 to 1, null when the post is not about the brand), is it sarcastic, which aspect it talks about (taste_or_quality, price_or_value, availability_or_delivery, health_or_safety, advertising_or_campaign, customer_service, none), and did the author buy or use it (first_hand). intent: what the author is mainly doing (label: asking_for_recommendation, comparing_options, switching_away, complaining, promoting, news_or_discussion, other, or null when unsure, with confidence), whether they read as a potential buyer rather than a seller (buyer, seller), how pressing the need is (urgency, 0 to 3), and, when you pass offer=, whether your offer would plausibly help them (fits_offer). niche: which of the 33 niches of the published taxonomy is-niche-v1 the caption belongs to, or personal_no_niche, or other (label, confidence, taxonomy), with label null when the caption is too thin to tell or the pick is unsure. It reads the caption only, not the video. quality: how much checkable detail the caption carries (fact_density 0 to 3), whether it mainly asks for likes, replies, shares, follows or tags (engagement_bait, 0 to 1), whether it is written to provoke anger as a way to get engagement (rage_bait, 0 to 1; about the writing, never the side taken), whether it only repeats someone else's news or view (secondhand, 0 to 1), and what the post is mainly doing (post_aim: inform, opinion, sell, entertain, provoke, other). exclude=engagement_bait drops posts whose engagement_bait is 0.8 or higher. injection flags text that addresses an AI system and tries to direct it (flagged, p); it never drops or rewrites a row. A post that could not be judged carries labels: null. Posts already labelled for anyone are free. data.labels reports what was judged and billed.
Optional CSV (engagement_bait), only with label=quality. Drops posts whose engagement_bait probability is 0.8 or higher and lists their ids in data.labels.dropped_ids. A post that could not be judged is never dropped.
Required by label=mention, ignored otherwise. The brand or product the posts are judged against, up to 300 characters, for example brand=Buldak. Without it label=mention is skipped with the warning label_mention_needs_brand and is not billed.
Optional, with label=mention. One plain sentence saying what the brand is, for example brand_description=Samyang's spicy instant noodle brand. Use it when the name is also an ordinary word or another company's name.
Optional, with label=intent. One or two plain sentences saying what you sell, up to 300 characters, for example offer=A web design agency that builds websites for small businesses. Adds fits_offer to every post; without it fits_offer is null.
Optional, on (the default) or off. By default every row gains free judgments (computed.labels, and computed.relevance on search endpoints), reported in data.labels (mode default) and data.relevance (origin default), each with a status (complete, partial or skipped) and pending: the rows still being judged when the page was sent, which carry null now and are filled on your next call or cached read. Default judgments never add credits, never change an existing field, and never drop or reorder a row. off returns the page exactly as before, with none of those keys. label=none does the same.
Value in
- "on"
- "off"
Optional. data.estimate reports rows_expected, rows_cached, label_credits_min, label_credits_max and base_credits. 0 credits charged.
Value in
- "1"
Optional, only with label=. When 1, every labelled row also carries computed.labels_evidence. = { quote, sentence_index }: the sentence in the row that most clearly shows the label, copied verbatim. Absent or null when no single sentence shows it.
Value in
- "1"
Optional. When goal, keep the rows and fields needed for the goal you pass in goal= (plus any that are uncertain, and the first and last), and replace the rest with a stub. data.held_back lists the held ids and a recall id that re-reads the full page from cache. Without this param the page is unchanged.
Value in
- "goal"
Required by fit=goal. What you are trying to do, in your own words, up to 300 characters.
Optional, only with fit=goal. Soft cap on how much of the page to keep, in tokens. Uncertain blocks and the first and last block are kept even if they exceed it.
Response Body
application/json
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application/json
curl -X GET "https://example.com/v1/twitter/user/tweets?handle=string"{ "success": true, "platform": "instagram", "endpoint": "/v1/instagram/profile/posts", "data": { "items": [ "…" ], "dropped": 0 }, "pagination": { "next_cursor": "is2.eyJwIjoyfQ", "has_more": true, "page_size": 12 }, "credits_used": 20, "credits_remaining": 9980, "request_id": "req_1a2b3c4d5e6f", "cached": false, "idempotent_replay": false, "charge_reason": "miss", "free_call": false}User › Media GET
Returns the tweets on an account's Media tab, only those carrying a photo or video, with media URLs, engagement counts, and creation time. View and bookmark counts are null here. Use it to pull an account's visual output without the text-only tweets user/tweets includes; the cursor pages deeper into the media grid. **20 credits** per call. Re-running the exact same call within 6h is free. Paginates by `cursor` — see [Pagination](/docs/pagination).
Channel › About GET
Returns the address behind a channel's View email address control on author.ext.public_email, its listed country, and the profile: id, handle, name, avatar, bio, URL, subscribers, join date, views. Use it for outreach when GET /v1/youtube/channel returned no email: that lane reads only the public description, this one reads the About tab control. Premium priced, so shortlist first. **500 credits** per call. Re-running the exact same call within 24h is free.