Read your X (Twitter) audience and niche from real data. Pull a handle's recent tweets (yours or a competitor's) with likes, replies, and views, see which formats and hooks are working, read the repliers on a tweet (X gates likers, so repliers are the signal), and scan a niche query for top tweets. Powered by Apify, no login.
SkillScore65Maintained
Automatic
◆Marketing & Content pack
Last verified 9/2/2026
What it changes
Passed 15 of 23 test cases with the skill, and 10 of 23 without it.
Without skill43%
With skill65%
Checks it passed that the model alone missed
States the cost as approximately $0.15 per 1,000 tweets.
Identifies x-reply-drafter as the skill for drafting responses.
Passes max_items=30 as the default limit for fetch_user_tweets.
and 4 more in the full report
6 fixed9 passed either way7 still failing1 broke
Pass-rate lift
+22 pp
Tokens
+64%
Agent turns
0%
Response time
+7%
Model gemini-3.6-flashMeasured 9/2/2026v115 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 6
Prompt
I want to scan X for top content around 'cybersecurity trends'. What specific function call should be executed to fetch the top tweets for this query?
What was checked, without and with the skill
Checked
Without skill
With skill
Calls fetch_niche_top to retrieve top tweets for the search query.
Missed
Passed
case-12 · gemini-3.6-flash · 9/2/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md64 linessingle file
X Audience Insights
Turn real X data into a read on what is working: which of your tweets landed and why, who is replying, and what the accounts in your niche are doing right now. This is the read layer, so the skill sees actual numbers instead of guessing.
One honest limit: X gates the list of who liked a tweet, so a full liker roster is not reliably available. The signal here is repliers + tweet performance, which on X carries the real conversation anyway.
When to use
"Analyze my last tweets / what is working for me"
"Read the replies on this tweet"
"What are [competitor / accounts in my niche] posting"
"Scan the niche for top tweets on [topic]"
Not for writing a tweet (use x-post-writer) or a thread (use x-thread-builder).
Setup (optional)
The read layer uses Apify (no login, no cookies). Get a free token at https://console.apify.com/account/integrations and set APIFY_TOKEN. The X actor costs about $0.15 per 1,000 tweets. No token? Paste the tweets or replies and the skill runs the same analysis on them.
Input
A handle (yours or a competitor's), a tweet URL, or a niche query
Optional: the goal (what is working / competitor read / niche scan)
Output
Performance read - the handle's recent tweets ranked by engagement, with the pattern behind the top ones (hook shape, length, format)
Replier read - who replied on a tweet, recurring questions, repliers worth a follow-back or a reply
Niche scan - top tweets for a query, the formats that travel right now
Action list - what to write more of, who to engage, what to reply to
Steps
Pull the data. For a handle: lib.ApifyClient().fetch_user_tweets(handle, max_items=30). For a tweet's repliers: fetch_tweet_replies(tweet_url). For a niche: fetch_niche_top(query, sort="Top"). Falls back to pasted data if no token.
Rank by engagement. Sort by likes + replies + views. Normalize against the author's follower count so a small account's breakout is not buried under a big account's average.
Extract the pattern. For the top tweets, name what they share: the hook shape (one-liner, data-point, confession), the length, single vs thread, the presence of a specific number. That is the repeatable part.
Read the repliers. Cluster replies into questions, agreement, and pushback. Recurring questions are content ideas; high-follower repliers are follow-back candidates; real questions with traction are reply candidates.
Scan the niche. From fetch_niche_top, surface the formats and angles that are traveling now (note when search returns thin, and lean on known-account pulls instead).
Build the action list. Write-more-of (the winning pattern), engage (specific repliers/accounts), reply-now (questions with traction). Route drafts to x-post-writer / x-reply-drafter.
Deliver the report in the Output shape, with the raw ranked tweets attached.