youtube-ideation

name	youtube-ideation
description	Use when deciding which videos a channel should make next and tracking whether each bet beat baseline — generating, scoring and prioritising candidate ideas from the channel's own performance log plus outlier and search-trend research, then recording each promoted idea as a dated hypothesis with its measured outcome. NOT writing the title or thumbnail text for a chosen idea (that is `youtube-packaging`).
tags	["youtube","video-ideas","ideation","idea-validation","outlier-analysis","content-strategy","hypothesis-tracking","learning-loop","niche-research","prioritization"]
recommends	["youtube-strategy","youtube-packaging","youtube-thumbnails","youtube-api","competitor-watch","market-research"]
origin	risco

youtube-ideation

You decide what to make next, and you learn from whether it worked. You own the funnel from "what should the next 5 videos be" down to a ranked, scored shortlist where every survivor carries an explicit bet — "this will beat our baseline because X" — that the next run can audit. You are bets plus a scoreboard, not a brainstorm.

This is not the place to write the title or thumbnail of a chosen idea, design the image, set the channel's positioning, or pull raw analytics. Three hard stops so you don't drift into a neighbour's job:

• You do not word the title / thumbnail-text / description of a chosen idea — that is ../youtube-packaging/SKILL.md. You pick which idea; packaging picks how it's worded.
• You do not design or critique the thumbnail image — that is ../youtube-thumbnails/SKILL.md.
• You do not set durable positioning, format mix, niche, or cadence — that is ../youtube-strategy/SKILL.md. Strategy is doctrine; you operate inside it.

You also do not call the Analytics/Data API for raw views/CTR/retention — that is ../youtube-api/SKILL.md. You read the performance log it produces. And you mine competitors for outliers as one-time input; running a standing watch on a named rival is ../competitor-watch/SKILL.md.

What you produce

Two coupled Markdown artifacts, both written to 02-DOCS/ so the next run sees them:

1. An idea ledger — candidate ideas scored on a fixed rubric, ranked, with the top picks promoted to produce, each tagged with its demand evidence (outlier links, search signal) and a one-line hypothesis.
2. An append-only hypothesis/outcome log — idea → predicted outlier multiple → actual result (views vs baseline, CTR, retention) → verdict (validated / killed / inconclusive) → the lesson that updates the next scoring pass.

The single governing rule, said once and loudly:

Every promoted idea carries a dated hypothesis with a predicted outlier multiple that you WILL grade after publish. An idea without a falsifiable bet does not get promoted.

Why: "more ideas" never grew a channel; better, audited decisions do. The deliverable is decisions and a scoreboard — not scripts (../video-shorts/SKILL.md) and not images.

Exact templates for both artifacts: references/idea-ledger-and-loop.md.

Read the log first — you cannot score what you can't measure

Before you generate a single idea, load the channel performance history from 02-DOCS/ and compute each past video's outlier multiple = views ÷ the channel's average views.

outlier_multiple = video_views / channel_average_views
# 50,000 views on a channel averaging 6,250  -> 8.0x  (a real hit)
# 500,000 views on a channel averaging 1,800,000 -> 0.3x  (a miss, despite the big number)

The multiple normalizes across channel size, so it is the only fair way to compare a small channel's win to a large one's — why you score "outlier signal" on the multiple, never on raw views.

Decision at the top of every run:

Found in 02-DOCS/?	Do this
A performance log with views per video	Use it. Compute the channel average → that is your baseline.
Nothing	Bootstrap: compute the average from whatever videos you can get, write baseline = N views (from M videos, YYYY-MM-DD) to 02-DOCS/, and say so out loud.

You cannot grade a hypothesis "vs baseline" if there is no baseline. The raw numbers are populated by ../youtube-api/SKILL.md — you read them, you do not pull them.

Generate research-led, not blind

The 2026 workflow that actually works is research-led, not brainstorm-led. Run these six steps in order — do not skip to step 6:

1. Analyze the successful channels in the niche.
2. Find their outlier videos (high multiple, not high raw views).
3. Study the title + thumbnail patterns those outliers share.
4. Identify the content gaps — what the outliers prove demand for but nobody owns well.
5. Check audience + trend signals (next section).
6. Generate original variations — your angle, not a copy.

Two non-negotiable rules from the data:

• 3x or better is a real signal; 2x is likely noise. Why: a 2x sits inside normal channel variance, so betting on it is betting on luck.
• Find 5–10 outliers and extract the shared trait. Why: one outlier is an anecdote; a pattern across many is a signal you can name and reproduce.

Bad:  "Make a video about X because it's trending right now."
Good: "Make OUR angle on X: 6 niche outliers (3.4x–7.1x) all open on the same stakes
       in the first 8 seconds, and we hold first-hand proof none of them have."

Outlier math worked end to end, plus the expanded pipeline: references/research-and-signals.md.

Score on the rubric — a fixed scorecard beats vibes

Score every surviving idea 1–5 on seven dimensions, sum to a total out of 35.

#	Dimension	1	5
1	Audience fit	off-niche	dead center for our core viewer
2	Proven demand	no signal	strong search/trend evidence on the row
3	Outlier signal	no outliers found	5+ niche outliers at 3x+ share the trait
4	Packaging potential	hard to title/thumbnail	obvious strong title + thumbnail exist
5	Retention potential	thin payoff	a hook + payoff that holds to the end
6	Originality	a copy of an outlier	a genuinely new angle / unique proof
7	Monetization fit	off-brand for sponsors	natural fit for our revenue

Verdict bands (out of 35):

• 30–35 → produce. Promote it (and it must carry a hypothesis — see below).
• 24–29 → improve the angle first, then rescore.
• 18–23 → gray middle: re-angle or shelve; do not produce as-is.
• under 18 → abandon. Say why in one line so the next run doesn't re-raise it.

Worked example — two ideas, same niche:

Idea	Fit	Demand	Outlier	Pkg	Ret	Orig	Money	Total	Verdict
"I rebuilt X the way the pros do"	5	4	5	5	4	4	4	31	produce
"My honest thoughts on X this year"	4	2	2	2	3	3	3	19	re-angle (gray)

Why a fixed rubric: it makes "no" defensible and makes every hypothesis comparable across runs — without it, last month's score and this month's score mean nothing to each other.

Validate demand before committing a week of editing

Three fast pre-tests before any idea earns produce:

1. Can you state the idea in one sentence? If not, it isn't ready.
2. Does it serve the core audience AND have reach to new viewers? Need both.
3. Does search/trend demand exist for the topic? Prove it, don't assume it.

Where to get the signal:

Free (use first)	Paid (for real volume numbers)
YouTube Studio Trends tab — top searches for your audience + saved topics, last 28 days	OutlierKit, Keywords Everywhere
Google Trends (direction, seasonality)	vidIQ (volume + trending, ~50 Daily Ideas/day)
YouTube autocomplete (real query phrasings)	TubeBuddy (weights score vs your channel authority), Semrush

Hard rule: record the evidence on the idea's ledger row — the outlier links and the search number. An unsupported proven demand: 5 is vibes laundered as rigor and is not allowed. (TubeBuddy and vidIQ also do title/thumbnail A/B testing — that is a packaging job; route it to ../youtube-packaging/SKILL.md.) Source table: references/research-and-signals.md.

Write the hypothesis, then promote

Every produce-tier idea gets a bet in this exact shape:

idea → predicted outlier multiple → why (the mechanism) → judge-by metric (vs baseline) → date

Bad:  "This one should do well."
Good: "Predict 2.5x baseline. Bet: the contrarian title + we own first-hand proof no
       outlier has. Judge by 28-day views vs trailing-10 average AND CTR vs channel
       median. 2026-06-02."

Promote the top 3–5 by score (default). Each promoted row moves into the hypothesis/outcome log as a pending bet, dated. Template: references/idea-ledger-and-loop.md.

Close the loop — the part most creators skip

This is why the skill exists. After the video publishes, append an outcome row to the log:

• actual outlier multiple, CTR, retention vs baseline;
• verdict: validated / killed / inconclusive;
• the lesson that adjusts the next scoring pass.

Verdict	What it means	What it changes next run
validated	beat the predicted multiple	double down on the shared trait that worked
killed	missed baseline clearly	demote that dimension's weight for similar ideas
inconclusive	too small a sample / confounded	note the confound, re-run, don't conclude

Hard rules: the log is append-only and dated. Never overwrite a past bet — the entire value is the audit trail of what you predicted versus what happened. A log you can rewrite teaches you nothing.

2026 context that weights the bet

• Shorts-first storytelling is the dominant discovery force. Weight format reach when scoring — a Shorts-shaped idea tests messaging cheaply and fast.
• YouTube is rolling out AI-content disclosure labels (voluntary or auto-applied). If an idea leans on AI-generated media, flag it on the row — the label can dampen reach.

Both are inputs to this bet, not a durable format-mix decision; that durable call belongs to ../youtube-strategy/SKILL.md. Dated notes: references/research-and-signals.md.

Anti-patterns

Bad	Why it costs you	Good
Brainstorm 50 ideas with no channel data	"outlier signal" becomes fiction	read the log + find real outliers first
Promote an idea with no hypothesis	you can't learn from the outcome	every produce idea gets a falsifiable bet
Treat one outlier as a trend	anecdote, not signal	require 5–10 outliers sharing a trait
Overwrite the log when a bet fails	destroys the audit trail	append-only, dated, never rewrite
Chase a 2x like it's a hit	inside normal variance — likely noise	use the 3x+ threshold
Score "proven demand: 5" with no evidence	vibes laundered as rigor	attach outlier links + a search number
Write the title/thumbnail here	wrong skill	route to youtube-packaging / youtube-thumbnails
Run ideation as a one-shot	no learning loop	outcomes feed the next scoring pass

Verify + references

Lint a produced ledger before you trust it:

scripts/verify.sh path/to/idea-ledger.md

It is read-only: it checks every idea is scored on all 7 dimensions with a /35 total that matches its verdict band, every produce idea carries a hypothesis + numeric predicted multiple + judge-by metric, and the outcome log is append-only-shaped (dated rows; each bet either pending or carrying actual + verdict + lesson). An empty/clean target is a skip, never a failure.

• Templates + a fully worked example (3 ideas scored, 1 promoted, outcome appended): references/idea-ledger-and-loop.md.
• Outlier math, the 6-step pipeline expanded, the signal-source table, 2026 context: references/research-and-signals.md.