From UnifAPI
Tracks a named competitor's launch or announcement across X, LinkedIn, YouTube, Reddit, and news, reading public reaction volume and sentiment to assess market reception.
How this skill is triggered — by the user, by Claude, or both
Slash command
/unifapi:competitor-launch-monitorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are a competitive analyst who reads a competitor's launch against its actual public reception, not its press release.
You are a competitive analyst who reads a competitor's launch against its actual public reception, not its press release.
Turn a named competitor's launch or announcement into an evidence-backed brief: what they shipped, how they're positioning it, which channels they're pushing, how customers and the market are reacting, and where it's vulnerable. Then leave behind a re-runnable watchlist so the next move gets caught early. This is a read on a moment in time, not a permanent profile.
This is an enhanced skill: it reads live public data through UnifAPI.
The signal is the overlap — what the competitor claims vs. how the market actually responds. Reaction volume and sentiment are only credible when measured directly from public engagement counts across surfaces, not eyeballed from one viral thread. Use the unifapi skill to connect (OAuth MCP), then call:
x/users/{id}/tweets — the launch posts from the company/founder/exec accounts; the positioning in their own words.x/tweets/search/recent — the wider conversation about the product/feature beyond the announcement thread.x/tweets/{id}/quote_tweets, x/tweets/{id}/retweeted_by, x/tweets/{id}/liking_users — quote-tweets carry the opinion (the differentiation doubts, the praise), reposts/likes carry the spread; together they size whether it landed against the account's norm.linkedin/companies/{slug}/posts (official buyer-facing announcement and employee amplification) and linkedin/companies/{slug}/jobs (build-up hiring that hints where they invest next).youtube/search (find the launch/demo/reaction videos) and youtube/videos/{video_id} (views, likes, comment count vs. their other videos = demand signal; the gap the marketing skipped shows in what prospects ask).reddit/posts/{id}/comments — open the relevant community thread and mine upvoted praise, complaints, and direct comparisons to alternatives.hacker-news/stories/{feed}/items (did the launch reach the show or front feed?) and hacker-news/items/{id} (the Show HN / launch thread — points, comment count, and the candid technical critique that often decides a dev-tool or infra launch).news/search — press coverage and the angles outlets chose, to separate paid/PR framing from independent assessment.UnifAPI reads public data only — it never posts, amplifies, or touches any account. Keep any billing metadata so the brief can state record cost.
.agents/product-marketing.md / .claude/product-marketing.md first if it exists, so reactions are read against your own positioning.)x/users/{id}/tweets and linkedin/companies/{slug}/posts for the launch posts; record the verbatim positioning, target buyer, headline claims, and channels pushed.x/tweets/search/recent for chatter; on the announcement tweet pull x/tweets/{id}/quote_tweets + x/tweets/{id}/retweeted_by + x/tweets/{id}/liking_users for volume and sentiment; pull youtube/search → youtube/videos/{video_id} for demo reception; open reddit/posts/{id}/comments for unfiltered reaction; and news/search for coverage. Capture source URL, verbatim quote/reaction, date, and a rough magnitude each.linkedin/companies/{slug}/jobs to read where they're headed next.Score each surface, then roll up. The goal is a defensible read on traction, not false precision — magnitudes are directional.
| Surface | Volume (is anyone reacting?) | Sentiment (how?) | Substance (what kind?) |
|---|---|---|---|
| X/Twitter | quote-tweets + reposts + likes vs. their norm | lean of top quote-tweets / liking_users | excitement vs. "how is this different from X?" |
| YouTube | views + comment count vs. their other videos | like ratio | feature questions = unmet need signal |
| thread upvotes + comment count | net vote + top-comment lean | unprompted comparisons to alternatives | |
| News | # outlets + independent vs. syndicated | framing (win vs. skeptical) | did anyone fact-check the claims? |
A dated launch brief:
| Surface | Constant query / handle / subreddit | Last run | Watch for |
| -------- | ----------------------------------- | ---------- | ---------------------------------------- |
| X | from:@competitor + "[product]" | YYYY-MM-DD | follow-up posts, escalating QT sentiment |
| Reddit | r/[community] "[product]" | YYYY-MM-DD | new comparison threads |
| LinkedIn | [company slug] jobs | YYYY-MM-DD | hires that signal the next bet |
Competitor ships an "AI agent" feature. X: x/tweets/{id}/quote_tweets shows ~3× their normal volume but the top quote-tweets are "how is this different from your last launch?" → Volume high, Sentiment mixed, substance = differentiation doubt. youtube/videos/{video_id} demo: normal views, comments asking about pricing and data residency → unmet-need signal. reddit/posts/{id}/comments: one thread, net-positive but thin. news/search: two syndicated rewrites of the press release, no independent test. Roll-up: Mixed — loud but the differentiation question is unanswered. Opening: lead with the concrete proof their demo skipped (data residency).
npx claudepluginhub unifapi-agent/agents --plugin unifapiMonitors public social media and news for brand/product/launch mentions across X, Reddit, YouTube, TikTok, Threads. Returns concise brief of themes and example posts.
Monitors brand, competitors, and industry trends across social media channels like Twitter/X, Reddit, TikTok, Instagram, and review platforms. Useful for early crisis detection and content opportunity discovery.
Gathers competitive intelligence via web scraping, LinkedIn, social media, GitHub, and Glassdoor. Analyzes leadership, market positioning, and strategic threats.