Executive Mention Tracker

SKILL: Executive Mention Tracker
An executive's reputation is shaped by what others say, not what they post. This watches mentions of a named leader across up to six networks at once and sorts them into wins to amplify and risks to get ahead of. You choose which surfaces to scan and how far back to look.

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:
  - exec_name (required): <exec_name — ASK THE USER>
      Full name of the executive to monitor
  - exec_linkedin_url (required): <exec_linkedin_url — ASK THE USER>
      LinkedIn profile URL or slug used to match LinkedIn mentions of the person
  - platforms (optional): (optional — e.g. youtube, facebook)
      Comma-separated list of platforms to run — options: linkedin, twitter, news, reddit, youtube, facebook. Omit to run all of them; name specific platforms to limit the run.
  - news_window (optional): 7d (default — override if you like)
      How far back to pull press mentions, mapped to search_news time_published. One of 1h, 1d, 7d, 1y, anytime. Defaults to 7d for a weekly brief; widen for a deeper retrospective.
  - pages (optional): 4 (default — override if you like)
      Result depth (number of pages) to pull per paginated social surface (X, YouTube, Facebook). Higher values catch more low-engagement chatter at the cost of speed. Defaults to 4.

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` — search_linkedin(mentions_member={exec_linkedin_url}, get_sentiment=true, sort_by=most_recent)
     Pull posts that tag the exec and split positive endorsements (wins) from negative posts (risk).
  2. Tool `search_twitter` — search_twitter(query="{exec_name}", get_sentiment=true, sort_by=most_recent, pages=4)
     Capture public chatter and flag anger/negative items with high engagement for review. Tune 4 to control how deep the sweep goes.
  3. Tool `search_news` — search_news(query="{exec_name}", time_published=7d, limit=30)
     Surface earned/press mentions over the chosen 7d (default 7d) and note outlet tone and reach.
  4. Tool `search_reddit` — search_reddit(query="{exec_name}", get_sentiment=true, sort_by=most_recent)
     Pull candid community threads and flag negative or anger-dominant posts as emerging risks.
  5. Tool `search_youtube` — search_youtube(query="{exec_name}", get_sentiment=true, upload_date=this_week)
     Only run if {platforms} includes youtube: catch interviews, conference talks, commentary and criticism videos that name the exec, and flag negative, high-view videos as reputation risks.
  6. Tool `search_facebook_posts` — search_facebook_posts(query="{exec_name}", get_sentiment=true, pages=4)
     Only run if {platforms} includes facebook: surface public Facebook chatter about the exec and flag negative posts as emerging risks.

DELIVER: A weekly executive-reputation brief that sorts every mention across the chosen networks into wins, neutral, and risks, with the highest-reach negatives (including YouTube videos and Facebook posts when enabled) flagged for response.

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.