twitter

---

name: twitter version: 2.0.2 description: | Twitter/X data: fetch tweets, search, user profiles, followers, replies, trends.

Use for any x.com or twitter.com URL or lookup (e.g. summarize this tweet, recent posts by @vitalikbuterin, search $SOL min_faves:50). delivery: script metadata: starchild: emoji: "🐦" skillKey: twitter requires: env: - TWITTER_API_KEY

user-invocable: false disable-model-invocation: false

---

Twitter / X (script-mode)

Read-only access to twitterapi.io endpoints. 13 functions covering tweets, users, followers, replies, threads, quotes, articles, and trends.

All requests go through sc-proxy via core.http_client.proxied_get. The TWITTER_API_KEY env var is auto-injected server-side, no local key needed on the agent machine.

Script Usage

Standard invocation pattern:

python3 - <<'EOF'
import sys, json
sys.path.insert(0, "/data/workspace/skills/twitter")
from exports import twitter_user_info, twitter_user_tweets

profile = twitter_user_info(username="vitalikbuterin")
print(json.dumps(profile, indent=2))

recent = twitter_user_tweets(username="vitalikbuterin")
print(f"got {len(recent.get('tweets', []))} tweets")
EOF

Tweet ID extraction from URL: the last path segment of any x.com/{user}/status/{id} or twitter.com/{user}/status/{id} URL is the tweet ID. Pass it as a string (Python int will lose precision on long IDs).

Function Reference (signatures)

All 13 functions live in exports.py. Returns are dicts straight from twitterapi.io — keys vary per endpoint, inspect once before scripting.

Tweet endpoints

Function	Description
twitter_search_tweets(query, cursor=None)	Advanced search. Operators: from:user, to:user, #tag, $cashtag, lang:en, has:media, has:links, is:reply, min_faves:N, since:YYYY-MM-DD, until:YYYY-MM-DD.
twitter_get_tweets(tweet_ids)	Fetch one or more tweets by ID. tweet_ids = list of strings (also accepts comma-string).
twitter_tweet_replies(tweet_id, cursor=None)	Replies to a tweet.
twitter_tweet_retweeters(tweet_id, cursor=None)	Users who retweeted.
twitter_tweet_thread_context(tweet_id)	Full thread context (parents + direct replies).
twitter_tweet_quote(tweet_id, cursor=None)	Quote tweets.
twitter_get_article(tweet_id)	Long-form X article body.
twitter_get_trends(woeid=None, country=None, category=None, limit=None)	Trending topics; all filters optional.

User endpoints

Function	Description
twitter_user_info(username)	Profile: bio, follower/following counts, tweet count, verified.
twitter_user_tweets(username, cursor=None)	User's recent tweets.
twitter_user_followers(username, cursor=None)	Follower list.
twitter_user_followings(username, cursor=None)	Accounts followed.
twitter_search_users(query, cursor=None)	Search users by name/keyword.

username is the handle WITHOUT @ (e.g. "elonmusk", not "@elonmusk"). Pagination: when a response includes next_cursor, pass it back as cursor on the next call.

When to use this skill

• ANY x.com/... or twitter.com/... URL → start here, NOT web_fetch (Twitter blocks scrapers).
• Single tweet detail → twitter_get_tweets([tweet_id]).
• "What's @user been posting?" → twitter_user_tweets.
• KOL discovery / cashtag mentions → twitter_search_tweets("$SOL min_faves:50").
• Trending topics → twitter_get_trends.

Billing & cost control (READ before bulk/scheduled use)

twitterapi.io bills per item actually returned, not per request and NOT by any "max_results" you ask for. sc-proxy charges = returned-item-count × unit (tweets 45 / profiles 54 / followers 45 credits; 100k credits = $1; 3× upstream). Min 1 item per request.

The last_tweets / user_tweets trap: the upstream /twitter/user/last_tweets endpoint has no page-size parameter — it always returns up to 20 tweets per page. There is no max_results / pageSize lever, and twitter_user_tweets() does not accept one. So "I only need 5" still fetches and bills for ~20. Slicing the result client-side does NOT save money — the charge is already counted at the proxy from the upstream response.

⭐ Polling for "new tweets from account X" → use search, NOT last_tweets

This is the biggest, most common waste. twitter_user_tweets() (upstream last_tweets) has no page-size param and always bills a full ~20-tweet page every call, even when nothing new was posted. The official twitterapi.io guide recommends the advanced_search endpoint instead, which our skill already exposes as twitter_search_tweets():

# Cheap polling pattern — bills only the tweets actually in the window.
# When NO new tweet exists, the call is billed as 1 item (not 20).
import time
since = int(last_check_unix)
until = int(time.time())
q = f"from:{handle} include:nativeretweets since_time:{since} until_time:{until}"
res = twitter_search_tweets(q)   # queryType defaults to Latest

Official pricing (upstream; our proxy bills 3×):

• tweets found → $0.00015 per returned tweet
• no tweets found → $0.00015 for the whole call (vs last_tweets' ~20× that)

Per-call cost in our billing makes the difference obvious:

• last_tweets → ~$0.009/call (20 tweets every time)
• advanced_search empty window → ~$0.00045/call (1 item) — ~20× cheaper

Frequency vs monthly cost (single account, upstream): hourly $0.11 · 30min $0.22 · 15min $0.43 · 5min $1.30 · 1min $6.48.

Other cost levers

• Use get_tweets([ids]) when IDs are known — pay only for those exact tweets, not a 20-item page.
• Followers/followings bill per returned profile (default page 200 → 200 billed). Only paginate as far as needed. For ID-only graph work use the bulk followers-IDs endpoint (lightweight).
• Tighten search queries (min_faves, since_time/until_time, lang) so fewer pages are needed.

Note: twitterapi.io also sells a managed stream/webhook product. We do NOT subscribe to it — do not use the /oapi/x_user_stream/* or /oapi/tweet_filter/* endpoints. For any account-monitoring need, the advanced_search polling pattern above is the correct and only approach here.

Error handling

• 402 Credits is not enough → upstream proxy credits exhausted; tell user to top up. Don't retry.
• 429 → rate limited; surface to user, don't auto-retry.
• 404 user not found → suggest verifying the handle spelling.

Version Policy (hard rule)

This skill is script-mode (delivery: script). It does NOT register runtime tools — agent must read_file SKILL.md and call functions via bash + python3. The legacy tools.py / __init__.py files are kept for backward compatibility but are no longer the preferred entry point.

Bump rules:

• Any signature change, env-var change, or sc-proxy contract change → MAJOR
• New function added, response schema clarified → MINOR
• Bug fix or doc-only change → PATCH