A YouTube content-gap research skill that compares what people search for with the quality, age, and relevance of existing videos. It can also help builders find underserved product opportunities.

Use it to find content ideas in a niche, assess competition, verify whether a topic is genuinely underserved, or discover product opportunities from unmet demand.

It helps identify topics with clear audience demand but weak, outdated, or poorly matched video coverage.

yt-gap — Skill for Claude Code by not0lucky

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add not0lucky/tubescout --skill yt-gap

Clone the repo

git clone --depth 1 https://github.com/not0lucky/tubescout

Made for: Claude Code.

Or install tubescout, the plugin that ships this one along with the rest of its 6 skills, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/not0lucky/tubescout/yt-gap/github.svg)](https://agentmods.dev/skills/not0lucky/tubescout/yt-gap)

Your own site

<a href="https://agentmods.dev/skills/not0lucky/tubescout/yt-gap"><img src="https://agentmods.dev/badge/skills/not0lucky/tubescout/yt-gap/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/not0lucky/tubescout/yt-gap"><img src="https://agentmods.dev/badge/skills/not0lucky/tubescout/yt-gap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 724 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00087	$0.00724
Opus 5	$0.00044	$0.00362
Sonnet 5	$0.00017	$0.00145
Haiku 4.5	$0.00009	$0.00072

Measured 11d ago against content hash a6c9d4186c25, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

yt-gap scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/yt-gap/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

yt-gap

Demand you can see, supply you can count — the gap between them is the opportunity. Works for two audiences: creators (what to publish) and builders (what to build).

Process

Map demand. get_search_suggestions on the seed term, then recurse into the 4–6 most specific suggestions (and language variants — Arabic/French/Spanish suggestions with thin English-style supply are double gaps). Autocomplete only shows queries with real volume; specificity = intent.
Measure supply per demand signal. For each promising query, search_videos (default sort) and check the top results:
- Freshness: are the top hits years old? (published fields)
- Fit: do titles actually answer the query, or only adjacent topics?
- Quality proxy: views relative to channel size where visible; clickbait vs substance.
- Volume: many strong recent hits = served; few/old/misfit = gap.
Verify the best 2–3 gaps. get_video on the top incumbent (age, engagement) and, if depth is needed, get_transcript to confirm the incumbent is actually weak or outdated — a gap that survives reading the competition is real.
Rank and frame. Each gap gets: the demand evidence (which suggestions, which view counts) / the supply weakness (old, misfit, thin) / the move (video topic + angle for creators, product angle for builders). Tailor to what the conversation says the user does — an n8n consultant gets automation gaps framed as content topics, a developer gets them framed as tool ideas.

Rules

Cite only URLs returned by tubescout tools in this conversation — never write a YouTube URL or video ID from memory.
A gap needs BOTH sides evidenced. High demand + strong supply = red ocean; no demand signal + no supply = probably no market, not a gap. Say which is which.
YouTube demand ≠ total market: some B2B niches search Google, not YouTube. Flag when the niche is likely one of those.
Recency window matters: check supply within the last year, not all time — a 2019 million-view video with no modern successor IS the gap.
12–16 tool calls is the normal budget (suggestions recursion + supply checks + 2–3 verifications); go deeper only if the user asks.

Read the full file on GitHub · 48 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

11d ago First seen · 48 lines · 87 tokens per session scan A a6c9d4186c25

Subscribe to this mod's changes

yt-gap is a skill published in the GitHub repository not0lucky/tubescout (0 stars, last pushed 15d ago), licensed MIT. It adds 87 tokens to every session and 724 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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yt-gap

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

yt-gap

Process

Rules

What this file has done since we first saw it

Other skills, from other repositories

youtube-research

opik-diagnose

client-scripts

split-to-prs

agreement-setup

planfix-api