X Twitter

x-twitter

The deterministic read path for public X (Twitter) data through UnifAPI. This is a Data Skill: it does not run a marketing job on its own — it names the concrete x/... operations, response shapes, and gotchas so any X-first workflow (KOL pricing, creator vetting, buying signals, competitor and listening work) reads from one known recipe instead of rediscovering the surface each time.

Read-only — eyes, not hands. It researches public X data and returns cited records; it never posts, replies, follows, or DMs, and UnifAPI never holds X credentials.

Use the unifapi skill for live evidence

Connect once through the shared unifapi skill (OAuth MCP), then call the operations below. The X integration is backed by RapidAPI SocialLab but the public contract uses X-style /x/... paths — do not use legacy /twitter/... paths. Keep any billing metadata so the output can state record cost.

Response contract

Single-entity endpoints return the object in data:

{
  "request_id": "unif_...",
  "data": {},
  "billing": { "records_charged": 1, "balance_remaining": 99 }
}

List endpoints return an array in data plus pagination:

{
  "request_id": "unif_...",
  "data": [],
  "pagination": { "has_more": false, "next_cursor": null },
  "billing": { "records_charged": 1 }
}

When pagination.has_more is true, pass pagination.next_cursor as the next request's pagination_token (next_token is also accepted). Always preserve billing when reporting cost.

Core operations

Need a field not listed here? Use the unifapi skill's get_operation to read the exact schema before calling — but pick the operation from this table, don't discover blind.

Workflow

The deterministic recipes. Pick the one that matches the job; each names exactly what to call.

1. Resolve a handle to a profile. Strip the leading @, then call x/users/by/username/{username}. Read data.id (needed for every per-user call below) and data.public_metrics.followers_count.
2. Read recent engagement. With the id from step 1, call x/users/{id}/tweets?max_results=10&exclude=replies. Compute engagement from each tweet's public_metrics (like_count, retweet_count, reply_count, quote_count, impression_count). Page with x/users/{id}/tweets?pagination_token={next_cursor} when has_more.
3. Trace who amplified a post. With a tweet id from step 2, call x/tweets/{id}/retweeted_by, x/tweets/{id}/quote_tweets, or x/tweets/{id}/liking_users to see who reposted, quoted, or liked it — the amplification and intent signal behind buying-signal, listening, and competitor work. Use x/users/{id}/liked_tweets for what a user engages with. Page via next_cursor.
4. Gauge audience quality. Call x/users/{id}/verified_followers; it returns the verified followers as a paginated list, not a ready figure. Measure its size against data.public_metrics.followers_count from step 1 — that verified share is the real-vs-inflated signal that feeds confidence and warnings in downstream pricing/vetting skills. Page via next_cursor for a fuller count.
5. Discover from a topic (no handles yet). Call x/tweets/search/recent?query=... for recent matching posts, or x/autocomplete?query=... for user/topic suggestions, then resolve the surfaced handles with step 1.
6. Map a network. Call x/users/{id}/followers or x/users/{id}/following for audience-overlap or reach work; page via next_cursor.
7. Read regional trends. Call x/trends/by/woeid/{woeid} for what's trending in a location (WOEID), e.g. for listening or content-timing.
8. Cite everything. Every figure ties back to the post or profile it came from; report billing.records_charged (or estimate when billing metadata is absent).