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.
Install
npx skillscat add lumeierecollection-blip/youtube/niche-discovery Install via the SkillsCat registry.
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)
- 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. - 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. - 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. - 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
- De-duplication. Check the new niche isn't a near-duplicate of an
already-configured channel's niche (compare againstconfig/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.