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youtube-discovery-research

youtube-discovery-research is a skill for Claude Code, Codex from tubealfred/mcp. It costs 50 tokens per session (526 once invoked), scanned A, original, MIT.

A research workflow for discovering public YouTube videos, channels, playlists, hashtags, Shorts, and current trends. YouTube is a video-sharing platform; this workflow helps explore what exists around a topic.

In plain words
What is it for?
Finding competitors, validating topics, scanning trends, studying search wording, and building lists of related videos or channels.
Why use it?
It helps map a market or topic and find relevant content without relying on the user's Google YouTube Data API quota.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 2repo 1mo ago A scan 50 tokens original MIT

Good fit Finding competitors, validating topics, scanning trends, studying search wording, and building lists of related videos or channels.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tubealfred/mcp/youtube-discovery-research
View source ↗ tubealfred/mcp tubealfred.com
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 tubealfred/mcp --skill youtube-discovery-research
Clone the repo
git clone --depth 1 https://github.com/tubealfred/mcp

Made for: Claude Code, Codex.

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.

agentmods badge for youtube-discovery-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/tubealfred/mcp/youtube-discovery-research/github.svg)](https://agentmods.dev/skills/tubealfred/mcp/youtube-discovery-research)
Your own site
<a href="https://agentmods.dev/skills/tubealfred/mcp/youtube-discovery-research"><img src="https://agentmods.dev/badge/skills/tubealfred/mcp/youtube-discovery-research/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.

agentmods 80×15 button for youtube-discovery-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/tubealfred/mcp/youtube-discovery-research"><img src="https://agentmods.dev/badge/skills/tubealfred/mcp/youtube-discovery-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 526 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.00526
Opus 5.5 $0.00020 $0.00210
Sonnet 5.5 $0.00010 $0.00105
Haiku 4.5 $0.00005 $0.00053

Measured 2mo ago against content hash 158ccea523be, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

youtube-discovery-research 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 2mo 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/youtube-discovery-research/SKILL.md · 39 lines

How it starts

The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.

YouTube discovery research with TubeAlfred

Use the hosted read-only MCP server at https://mcp.tubealfred.com/. TubeAlfred provides public YouTube discovery data without changing YouTube accounts or requiring the user's Google YouTube Data API quota.

Select an entry point

  • Use youtube_search_query for a natural-language topic or named competitor.
  • Use youtube_search_hashtag for a hashtag-specific question.
  • Use youtube_trending_videos or youtube_trending_shorts only when the user asks what is currently trending.
  • Use youtube_search_suggestions to inspect query phrasing and adjacent audience language.
  • Use youtube_url_resolve when the supplied URL could represent a video, channel, playlist, or another YouTube resource.
  • Use playlist and channel tools after discovery to inspect a selected result in depth.

Expand deliberately

Search and related list operations can return continuation tokens. Fetch another page only when the requested result count, diversity, or confidence requires it. For large comparisons, collect identifiers first and use youtube_videos_batch or youtube_channels_batch rather than issuing avoidable one-by-one calls. Batch calls cost credits per successfully resolved identifier.

Research method

  1. Record the query, hashtag, region, or trend surface used.
  2. Build a candidate set before enriching individual results.
  3. Deduplicate repeated videos, channels, and playlists.
  4. Compare public metadata on a consistent basis such as publication time, topic, duration, channel, and available engagement fields.
  5. Use transcripts or comments only for shortlisted results and only when the user's question needs that evidence.
  6. Distinguish search ranking, recommendation adjacency, and trending placement; they are different discovery signals.

Boundaries

Search results are time-, region-, and upstream-dependent. Do not present a snapshot as permanent ranking truth. Do not infer private keyword volume, impressions, click-through rate, viewer cohorts, or causality from public discovery data. Respect Retry-After, stop on permission or unavailable-data outcomes, and avoid repeating successful calls because they can consume credits.

Read the full file on GitHub · 39 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.

  1. 2mo ago First seen · 39 lines · 50 tokens per session scan A 158ccea523be

Subscribe to this mod's changes

youtube-discovery-research is a skill published in the GitHub repository tubealfred/mcp (2 stars, last pushed 1mo ago), licensed MIT. It adds 50 tokens to every session and 526 once invoked, about $0.0002 per session on Opus 5.5. 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.

Claude CodeResearchchatgptclaudemcpmcp-serveryoutube
Related

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