---
name: youtube-ideation
description: "Use when deciding which videos a YouTube channel should make next and tracking whether each bet beat baseline — generates, scores, and prioritizes candidate ideas from the channel's own performance log plus outlier/search-trend research, then records each promoted idea as a dated hypothesis with its measured outcome. Use when asked to rank the next 5 videos, score a batch of ideas down to what's worth producing, find 3x+ outliers and content gaps in a niche, or validate demand before committing a week of editing. Triggers: 'what should my next videos be', 'score these ideas and tell me which to make', 'find content gaps and outliers in my niche', 'my last video flopped, log it and adjust what we pick next', 'which of our past bets actually beat baseline and what's the pattern', 'qué vídeo grabo ahora', 'dame ideas priorizadas para mi canal', 'valida esta idea antes de grabar', 'registra que este vídeo funcionó'. NOT writing the title/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**.

```text
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.

```text
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:

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

```text
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:

```bash
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`.
