lumeierecollection-blip

niche-discovery

Use to find and evaluate new channel niches when scaling the number of channels (e.g. going from 5 to 50). Combines YouTube trend data with web/social research to pick niches that are currently performing well AND likely to stay relevant, then recommends a video style per niche. Never invents a niche or its supporting numbers.

lumeierecollection-blip 0 Actualitzat fa 3 mesos
GitHub

Instal·la

npx skillscat add lumeierecollection-blip/youtube/niche-discovery

Instal·la des del registre de SkillsCat.

SKILL.md

Niche Discovery Skill

Purpose

Pick each additional channel's niche from real, current data — not from a
generic "good niche ideas" list. Every niche recommended here must trace
back to an actual search result.

Process (per candidate niche)

  1. Broad category sweep. Search YouTube (via trend-research) across
    candidate categories not already covered by existing channels — pull
    real view counts, upload frequency, and recency for top channels/videos
    in each.
  2. Durability check (separate pass, don't skip this). Search the web
    for whether this category is a short-lived spike (one viral event) or
    has a track record of sustained interest — look for multi-month/year
    search or view trend signals, not just this week's numbers. A niche
    that's only hot because of a single recent event should be flagged as
    lower-durability, not silently excluded or included.
  3. Practitioner/community check. Search what other automation/niche
    YouTubers say about this category's monetization and audience
    durability — this is a real signal, cite it, don't guess at it.
  4. Style fit. Based on what the actual top-performing videos in that
    niche look like (checked via search, not assumed), recommend one of the
    three existing styles:
    • fact/list/stat-heavy content → minimal
    • narrative, personal, or emotionally-driven content → the researched
      third style (see remotion-render skill — determined by research, not
      fixed in advance)
    • process/explainer/how-it-works content → motion-graphics
  5. De-duplication. Check the new niche isn't a near-duplicate of an
    already-configured channel's niche (compare against config/channels.json).

Output (per niche, before creating any channel config)

  • Niche name
  • Evidence it's currently performing well (with real numbers/sources)
  • Evidence for or against durability (explicit, not assumed)
  • Recommended style + why
  • Any practitioner/community notes found

Log this to a niche-candidates.md (or similar) file in the repo as each
niche is confirmed, so there's a durable record of why each channel's
niche was chosen — don't only put this in chat output.

Rules

  • Never propose a niche without at least one real search backing the
    "currently performing well" claim and a separate real search backing
    the durability claim — these are two different questions, don't
    conflate them into one search.
  • Never fabricate view counts, growth percentages, or trend language —
    if a number wasn't returned by an actual API/search call, don't state a
    specific number at all; describe it qualitatively instead ("multiple top
    videos in the last month" rather than a made-up percentage).
  • If fewer than 45 niches turn up strong evidence, report that back rather
    than padding the list with weak candidates — quality over hitting the
    exact number.