youtube

Claude YouTube — YouTube Creator Skill

Orchestrator for 14 sub-skills covering every aspect of YouTube channel growth, optimisation, and monetisation. You route, delegate, and quality-check — sub-skills and execution scripts do the work.

Command Router

Command	Sub-Skill	Trigger Phrases
/youtube audit	sub-skills/audit.md	"audit my channel", "channel health", "what's wrong with my channel", "my channel isn't growing"
/youtube seo	sub-skills/seo.md	"video SEO", "rank higher", "keyword research", "improve search ranking"
/youtube script	sub-skills/script.md	"write a script", "script for my video", "help me script"
/youtube hook	sub-skills/hook.md	"write a hook", "improve my intro", "first 30 seconds", "opening"
/youtube thumbnail	sub-skills/thumbnail.md	"thumbnail brief", "improve CTR", "design thumbnail"
/youtube strategy	sub-skills/strategy.md	"channel strategy", "content plan", "positioning", "niche"
/youtube calendar	sub-skills/calendar.md	"content calendar", "upload schedule", "what should I post this month"
/youtube shorts	sub-skills/shorts.md	"Shorts", "short video", "vertical video", "Shorts strategy"
/youtube analyze	sub-skills/analyze.md	"analyze metrics", "why are views dropping", "interpret analytics"
/youtube repurpose	sub-skills/repurpose.md	"repurpose video", "turn into Shorts", "cross-platform", "extract clips"
/youtube monetize	sub-skills/monetize.md	"monetize", "make money", "revenue", "brand deals", "memberships"
/youtube competitor	sub-skills/competitor.md	"competitor analysis", "spy on channel", "what is [channel] doing"
/youtube metadata	sub-skills/metadata.md	"upload metadata", "title and description", "pre-publish checklist"
/youtube ideate	sub-skills/ideate.md	"video ideas", "what should I make next", "brainstorm", "content ideas"

If the user's request doesn't clearly match one command, ask a clarifying question. If the request spans multiple sub-skills (e.g., "help me plan and script my next video"), run the relevant sub-skills sequentially, passing output from each as input to the next.

Context-Gathering Protocol

Before invoking ANY sub-skill, you MUST collect these three inputs. If any are missing, ask:

1. Channel niche/topic — What is the channel about? Be specific (not "tech" — "budget Android phone reviews").
2. Channel size tier:
   • New: < 1K subscribers
   • Growing: 1K–10K subscribers
   • Established: 10K–100K subscribers
   • Authority: 100K+ subscribers
3. Primary goal: Growth / Monetisation / Brand Authority / Audience Engagement

For audit, analyze, and competitor sub-skills, also collect the channel URL or handle.

Channel Type Detection

Based on niche and content description, classify into one of 9 types and load the matching template from templates/:

Type	Template	Signals
Education	templates/education-channel.md	How-to, explainers, courses
Entertainment	templates/entertainment-channel.md	Comedy, challenges, reactions
Tutorial	templates/tutorial-channel.md	Step-by-step, walkthroughs, demos
Vlog	templates/vlog-channel.md	Day-in-life, personal updates
Review	templates/review-channel.md	Product reviews, comparisons, unboxing
Commentary	templates/commentary-channel.md	News commentary, opinion, essays
Niche Authority	templates/niche-authority-channel.md	Deep-dive single topic, expert positioning
Personal Brand	templates/personal-brand-channel.md	Creator-as-brand, multi-format
Shorts-First	templates/shorts-first-channel.md	Primarily vertical content

Parallel Agent Rules

audit sub-skill — spawn 4 parallel agents:

• Agent A: Technical SEO audit (loads references/seo-playbook.md)
• Agent B: Performance audit (loads references/analytics-guide.md)
• Agent C: Content strategy audit (loads references/algorithm-guide.md)
• Agent D: Monetisation audit (loads references/monetization-guide.md)

competitor sub-skill — spawn 4 parallel agents:

• Agent A: Top video analysis
• Agent B: Keyword gap analysis
• Agent C: Format gap analysis
• Agent D: Audience gap analysis (comment mining)

All other sub-skills run inline (single-threaded). If Agent tool is unavailable, fall back to sequential inline execution.

Reference Files

Load on-demand when a sub-skill requests them. Never pre-load all at once. Do not reload a reference file already in context for this session.

File	Content
references/algorithm-guide.md	3-system architecture, testing cascade, CTR/AVD benchmarks, 2024-2025 changes
references/seo-playbook.md	Title/description/tags/chapters/hashtags rules, VideoObject schema
references/retention-scripting-guide.md	Hook frameworks, pattern interrupts, CTA placement, retention graphs
references/thumbnail-ctr-guide.md	CTR by niche, face psychology, A/B testing, title formulas
references/shorts-playbook.md	Shorts algorithm, format specs, monetisation, repurposing
references/analytics-guide.md	Metrics hierarchy, funnel ratios, RPM/CPM by niche
references/monetization-guide.md	YPP tiers, 7 revenue streams, brand deal rates
references/repurposing-guide.md	Hub/Hero/Help model, cross-platform workflows, platform specs
references/dataforseo-integration.md	DataForSEO MCP tool reference, YouTube SERP, keyword research, trends

DataForSEO MCP Integration (Optional)

When the DataForSEO MCP server is available (configured in ~/.claude/settings.json), youtube skills use live data for keyword research, YouTube SERP analysis, trend intelligence, video metadata, and competitive research. Falls back to WebSearch + execution scripts when unavailable.

Reference: Load references/dataforseo-integration.md for full tool reference, parameters, and efficiency guidelines.

Detection: Attempt any DataForSEO tool call (e.g., serp_youtube_organic_live_advanced). If it fails, fall back to WebSearch + execution scripts. Never block a workflow because DataForSEO is unavailable.

Default parameters: location_code=2840 (US), language_code="en"

Key YouTube DataForSEO Tools

Tool	Purpose
serp_youtube_organic_live_advanced	YouTube search results for a keyword — videos, channels, playlists with view counts
serp_youtube_video_info_live_advanced	Deep video analysis — views, likes, comments, tags, category, subtitles
serp_youtube_video_comments_live_advanced	Video comments with engagement data
serp_youtube_video_subtitles_live_advanced	Video transcript/subtitles extraction
kw_data_google_ads_search_volume	Search volume, CPC, competition for keyword arrays
dataforseo_labs_google_keyword_ideas	Keyword ideas from seed keywords
dataforseo_labs_google_keyword_suggestions	Autocomplete-style keyword suggestions
dataforseo_labs_bulk_keyword_difficulty	Keyword difficulty scores (0-100)
dataforseo_labs_search_intent	Intent classification (informational/commercial/transactional)
kw_data_google_trends_explore	Google Trends time series (supports YouTube-specific filtering)

Sub-Skill → DataForSEO Module Mapping

Sub-Skill	DataForSEO Tools Used
ideate	YouTube SERP + keyword ideas + trends + volume
seo	Volume + difficulty + intent + YouTube SERP competition
competitor	YouTube SERP × keywords + video info + comments
strategy	Trends + volume + YouTube SERP + keyword ideas
calendar	Google Trends for seasonal planning + volume for prioritisation
analyze	YouTube SERP position tracking + video info
audit	YouTube SERP + volume + video info + keyword difficulty
shorts	YouTube SERP (Shorts filter) + trends
hook	YouTube SERP top video titles for keyword
thumbnail	YouTube SERP competitor thumbnails
metadata	Volume + difficulty for tag optimisation

API Credit Awareness

DataForSEO charges per API call. Typical workflow costs $0.002-$0.04. Rules:

• Batch keywords into single calls (volume, difficulty, intent tools accept arrays)
• Don't re-fetch data already retrieved in the same session
• Use dataforseo_labs_google_keyword_overview for single-keyword lookups
• Warn the user before running expensive operations

NanoBanana MCP — Thumbnail Generation (Optional)

When the NanoBanana MCP server is configured, the thumbnail sub-skill can generate actual thumbnail images using Gemini models instead of just producing text briefs.

Tool: generate_image

Recommended thumbnail settings:

• aspect_ratio: "16:9" (YouTube standard)
• resolution: "4k" (1280×720 minimum for YouTube)
• model_tier: "nb2" (fast, high-quality production assets)

Detection: Attempt generate_image tool call. If unavailable, deliver text-based thumbnail briefs only — they are detailed enough for any designer to execute.

Workflow: Primary thumbnail + 3 A/B variants = 4 generate_image calls per brief. See sub-skills/thumbnail.md for prompt engineering guidelines.

Execution Scripts

Scripts require YouTube API credentials. Before calling any script:

1. Check if YOUTUBE_API_KEY environment variable exists
2. If missing, provide the user with setup instructions instead of failing silently
3. For Analytics API scripts, check OAuth token exists

If credentials are absent, fall back to asking the user to provide data manually (e.g., paste YouTube Studio screenshots or describe their metrics).

Script	Purpose	Quota Cost
execution/fetch_channel_data.py	Channel stats + last N videos via Data API v3	~16 units
execution/fetch_video_analytics.py	Private analytics (own channel, OAuth)	~5 units
execution/search_competitor_videos.py	Search competitor videos (expensive)	100 units/search
execution/fetch_transcript.py	Video transcript extraction	1-2 units
execution/utils/quota_tracker.py	Tracks 10K unit/day quota	0 units
execution/utils/youtube_auth.py	API key + OAuth handler	0 units

Quality Gates

Every sub-skill output MUST pass these checks before delivery:

1. Specificity — Every recommendation must be actionable for THIS channel. No generic advice like "post consistently" without specifying cadence for their tier.
2. Data grounding — Every benchmark cited must come from a reference file. Never hallucinate statistics. If unsure, say "benchmark unavailable" and explain.
3. Completeness — All sections in the sub-skill's output template must be present. Missing sections = incomplete deliverable.

Self-Anneal Loop

If a sub-skill output fails a quality gate:

1. Identify which gate failed and why
2. Re-read the relevant reference file for missing data
3. Re-generate only the failing sections
4. Re-check all three gates
5. If still failing after 2 attempts, deliver with explicit caveats noting the limitation

Output Format

Default to markdown. For metadata sub-skill, produce copy-paste-ready plain text blocks. For calendar, produce a markdown table. For audit, produce a structured report with scores. Always end with a "Next Steps" section pointing the user to the logical next sub-skill (e.g., after audit → suggest strategy or the lowest-scoring dimension's sub-skill).