Competitor Conquest Radar

SKILL: Competitor Conquest Radar
Turns a competitor's name into a live feed of their unhappy users — on LinkedIn via the mentions_company filter, and optionally on X and Reddit via keyword search — using AI sentiment to keep only the negative posts, then qualifies each person before you reach out.

You are running this skill on API Direct via its MCP tools. Execute the steps below yourself by calling the named tools in order — values in <angle brackets> come from a previous step. Then deliver the result described at the end.

INPUTS:
  - competitor (required): <competitor — ASK THE USER>
      The rival brand/company to monitor.
  - your_product (optional): (optional — e.g. Coda)
      Your product, so the agent can judge fit.
  - platforms (optional): (optional — e.g. linkedin, twitter, reddit)
      Comma-separated list of platforms to run — options: linkedin, twitter, reddit. Omit to run all of them; name specific platforms to limit the run.
  - sort (optional): most_recent (default — override if you like)
      Result ordering applied to every search step (maps to each tool's sort_by). most_recent surfaces the freshest complaints; relevance surfaces the closest keyword matches. Defaults to most_recent.

PLATFORM SELECTION: some steps are gated with "Only run if {platforms} includes X". If the user supplied a `platforms` value, run only the steps whose platform is listed. If the user did NOT supply `platforms`, run ALL steps — every platform the skill supports.

STEPS:
  1. Tool `search_linkedin_companies` — search_linkedin_companies(query="{competitor}")
     Run if {platforms} includes linkedin (the default). Resolve the competitor to its numeric LinkedIn company_id (take the best-matching result).
  2. Tool `search_linkedin` — search_linkedin(mentions_company=<company_id>, get_sentiment=true, sort_by=most_recent)
     Only run if {platforms} includes linkedin: Pull posts that mention the competitor. Keep only posts where sentiment.polarity == "negative" (dominant_emotion anger/disgust/sadness are the hottest).
  3. Tool `linkedin_person_posts` — linkedin_person_posts(url=<author_url>)
     Only run if {platforms} includes linkedin: For each promising LinkedIn complainer, read their recent posts to confirm they fit your ICP before outreach.
  4. Tool `search_twitter` — search_twitter(query="{competitor}", get_sentiment=true, sort_by=most_recent)
     Only run if {platforms} includes twitter: Search X for public complaints about {competitor} (try variants like "{competitor} switching OR cancel OR frustrated"). Keep only negative-sentiment posts; the author handle is your prospect, and the tweet text is your why-they-fit context.
  5. Tool `search_reddit` — search_reddit(query="{competitor}", get_sentiment=true, sort_by=most_recent)
     Only run if {platforms} includes reddit: Search Reddit for complaints about {competitor}. Keep only negative-sentiment posts; capture the username and subreddit as ICP context, and dedupe anyone already found on LinkedIn or X.

DELIVER: A ranked list of qualified prospects across LinkedIn (and optionally X/Twitter and Reddit) — name or handle, profile/post URL, what they complained about, and why they fit — newest and angriest first.

Note: each underlying tool call is billed at its normal endpoint price; get_sentiment adds a small per-page surcharge. Page through results as needed but stop once you have enough to deliver the outcome.