Reddit Deep-Expertise Sourcer

SKILL: Reddit Deep-Expertise Sourcer
The best engineers rarely job-hunt, but they answer hard questions in public. Mining the top answers to a deep technical problem across Reddit, specialized forums and X reveals demonstrated competence, and per-platform vetting filters down to credible, established accounts worth a cold approach.

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:
  - problem (required): <problem — ASK THE USER>
      A deep, specific technical problem only a real expert would answer well
  - skill_area (optional): (optional — e.g. Kubernetes)
      Broader skill area to widen the expert pool and spot recurring names
  - platforms (optional): (optional — e.g. reddit, forums, twitter)
      Comma-separated list of platforms to run — options: reddit, forums, twitter. Omit to run all of them; name specific platforms to limit the run.
  - time_window (optional): year (default — override if you like)
      Freshness window for the forums sweep, to bias toward currently active experts (maps to the forums time param)
  - result_depth (optional): 3 (default — override if you like)
      How many pages to pull per Reddit/X search to widen the candidate pool (maps to the pages param)

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_reddit_comments` — search_reddit_comments(query={problem}, sort_by=top, get_sentiment=true, pages=3)
     Gather the most upvoted, substantive Reddit answers to the hard problem and note the authors who show first-hand expertise. Raise 3 to widen the candidate pool.
  2. Tool `search_reddit_comments` — search_reddit_comments(query={skill_area}, sort_by=top)
     Widen to the broader skill area to spot authors who recur across multiple deep threads, signaling genuine depth.
  3. Tool `search_reddit_users` — search_reddit_users(query=<comment_author>)
     Vet each recurring Reddit author's karma and account age to keep only established, credible experts and drop throwaway accounts.
  4. Tool `search_forums` — search_forums(query={problem}, get_sentiment=true, time=year)
     Only run if {platforms} includes forums: sweep specialized technical forums — where the deepest written Q&A lives — for first-hand answers to the same problem, optionally bounded to year to favor currently active experts.
  5. Tool `search_twitter` — search_twitter(query={problem}, sort_by=relevance, get_sentiment=true, pages=3)
     Only run if {platforms} includes twitter: surface experts publicly answering the hard problem in threads and replies, ranked by relevance, and note the handles that recur.
  6. Tool `search_twitter_users` — search_twitter_users(query=<twitter_handle>)
     Only run if {platforms} includes twitter: vet each recurring X author by follower count and verification to keep only credible, established voices before a cold approach.

DELIVER: A vetted, deduped list of passive subject-matter experts who publicly solve {problem}-class issues — sourced from Reddit and, when enabled, technical forums and X — ranked by demonstrated depth and account credibility.

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.