Skill: charlie-morrison/youtube-channel-launch-coach (version 1.0.0)

--- name: youtube-channel-launch-coach description: Coach a creator from "I want to start a YouTube channel" through the first 1000 subscribers, monetization, and growth past the algorithm cliffs. Diagnoses why a channel isn't growing, why CTR is low, why retention drops, why monetization stalled. Knows the 2026 YouTube playbook: shorts vs long-form economics, browse-feed vs search-feed strategy, AI-content rules, Members vs Patreon. Adjusts advice for niche, format, and creator availability. Use when asked to launch a YouTube channel, validate a channel idea, write video titles or thumbnails, plan a content calendar, diagnose stalled growth, monetize, decide between long-form and shorts, structure a video, or migrate from Twitch/TikTok to YouTube. Triggers on "youtube channel", "youtube growth", "youtube monetization", "youtube shorts", "long-form vs shorts", "video title", "video thumbnail", "youtube algorithm", "stalled growth", "first 1000 subs", "AdSense YouTube". metadata: tags: ["youtube", "video", "creator-economy", "channel-growth", "shorts", "monetization", "content-strategy"] --- # YouTube Channel Launch Coach Coach a creator from "I have a camera and an idea" to a real channel — through the unglamorous middle of the first 6–18 months where most channels die. Built for creators who want growth backed by data, not vibes. ## Usage **Basic invocation:** > Help me launch a YouTube channel about [topic] > Why isn't my channel growing? > Should I focus on Shorts or long-form? > Critique my last video > Plan my first 30 videos **With context:** > Topic: software engineering interviews. 12 videos, 240 subs in 6 months, avg 1.2k views. > Niche: home espresso. 4k subs, monetized, growth stalled at 80–120/wk. > Migrating from TikTok (180k followers) to YouTube long-form. Comedy/storytime. > Want to build a faceless channel about historical battles using AI tools. The coach assesses where the channel is, what the bottleneck is (idea, format, packaging, retention, or distribution), and returns a concrete plan. ## Stage Diagnosis | Stage | Subs | Symptom | Right play | |---|---|---|---| | **Pre-launch** | 0 | Idea phase | Niche validation, format selection, brand strategy | | **Setup** | 0–100 | First 5–15 videos | Iterate on packaging, learn from analytics | | **Cliff #1** | 100–1000 | Growth slow | Find one outlier video pattern, double down | | **Monetization gate** | 1000+ | Approaching 4k watch hours | Consistency, batch production | | **Growth phase** | 1k–10k | Real audience | Algorithm push if packaging strong | | **Cliff #2** | 10k–50k | Plateau | Niche too tight, need format expansion | | **Established** | 50k+ | Channel works | Brand, business, optimization | ## Niche Validation A YouTube channel that survives is one where: 1. **You can produce 100 videos** without exhausting topic depth 2. **There is search/browse demand** (not just your friends interested) 3. **Existing channels prove it's viable** (3–10 channels with 50k+ on similar topics = market exists) 4. **Your unique angle is clear in the first 30 seconds of any video** Validation tools: - **YouTube search:** type topic phrases. Suggested searches show what people actually look for. - **VidIQ / TubeBuddy:** free tier shows channel scores in a niche. Aim for niches where top channels have 100k–2M subs (proven) but niche score is medium (room to grow). - **Channel teardown:** pick 3 channels in target niche, study top 10 videos each. What patterns repeat? **Niche red flags:** - Topic with one giant channel (e.g., MKBHD in tech) — no air to compete - Topic with no monetization fit (CPM <$3, sponsor pool small) - Topic that requires 6+ months to learn before you can produce - Topic where "personality" is the value and you don't enjoy being on camera ## Format Selection Three viable models in 2026: ### Long-form (8–25 min) - **Audience:** Browse-feed and search - **Pros:** Higher RPM ($3–$30 CPMS), watch hours quickly, deep audience, sponsor ready - **Cons:** Slow growth (months between subs spike), production-heavy - **Subs to monetize:** 1000 + 4000 watch hours (12 months) — typical 6–14 months - **Best for:** education, deep entertainment, finance, gaming reviews, video essays ### Shorts (60s) - **Audience:** Recommendation feed, viral - **Pros:** Fast feedback, can hit millions of views, build subs fast - **Cons:** Lower RPM ($0.05–$0.15), viewer loyalty weak, sub-to-watch conversion poor - **Subs to monetize:** 1000 + 10M Shorts views (90 days) - **Best for:** comedy, hooks, snackable info, building top-of-funnel for long-form ### Hybrid (Shorts → long-form pipeline) - **Approach:** Shorts for reach, long-form for depth and revenue - **Tradeoff:** complexity high, but compounds well at 10k+ subs - **Best for:** creators who already know the topic well and have endurance The coach helps choose based on creator's time, niche economics, and personality. ## Packaging: Title + Thumbnail (the only thing that matters at first) YouTube's algorithm gives every new video a small impressions test. CTR (click-through rate) determines whether it gets more impressions. A video with great content and bad packaging dies in 24 hours. **CTR benchmarks:** - 4–6%: average - 6–8%: good - 8–12%: excellent - 12%+: outlier (algorithm boost likely) **Title rules:** - 50–70 characters max (mobile cuts off) - Specific number > generic ("8 mistakes" > "common mistakes") - Curiosity gap, not lying clickbait - Emotional charge ("I was wrong about" / "the truth about" / "what nobody tells you") - Avoid: ALL CAPS, multiple punctuation, brackets unless very intentional **Thumbnail rules:** - 3–4 elements max (face, text, object, color block) - Face with strong emotion if you're a personality channel - High contrast (one color dominates) - Text 3–5 words, sans-serif, bold, drop-shadow or stroke - Mobile preview check (it'll be 200px wide) - Pattern interrupt: different from competing thumbnails **Title/thumbnail are linked:** - Thumbnail asks the question, title answers it (or vice versa) - Don't repeat the title in the thumbnail - The combo creates the curiosity gap that earns the click ## Retention: the second metric that matters Once you earn the click, the algorithm watches whether viewers stay. Average view duration (AVD) and audience retention curves drive distribution. **Retention benchmarks:** - AVD 50%+ on 10-min video = strong - AVD 40–50% = average - AVD <40% = re-think structure - Drop-off cliffs in first 30 seconds = bad opening - Drop-off in middle = pacing issue **Structure that holds attention:** ``` 0:00–0:15: HOOK - Tease the payoff - Visual energy - One specific claim that creates a question 0:15–0:45: PROMISE - What this video will deliver - Why watch the whole thing 0:45–end: BODY - 4–7 segments - Pattern interrupts every 60–90 seconds (cuts, b-roll, music change) - Each segment ends with a small payoff that tees up next End-15s: CTA - Subscribe + next video link ``` **Retention killers:** - Long intro (channel logo, music) — viewers leave during this - Slow opening setup before the topic - Monotone audio - Static shot for >30 seconds - "Today we're going to talk about..." preamble ## Production Quality and Tier Don't aim for cinematic in your first 50 videos. Audio quality is the only non-negotiable. | Tier | Setup | When | |---|---|---| | Bedroom | Phone + Rode VideoMic + window | First 30 videos | | Budget studio | Camera ($600 used) + lavalier mic + key light | Earning $/month | | Pro | Cinema camera + audio interface + multi-cam | At scale (>50k subs) | **Don't:** - Buy gear before posting first video - Re-record for one bad take (edit it) - Match $10M YouTuber production at 50 subs - Skip captions (most platforms add automatically; review for errors) ## First 30 Videos: The Real Plan The harsh truth: your first 10–15 videos probably won't grow. Treat them as paid education. ``` Videos 1–5: Find your face on camera. Topics you know cold. Videos 6–10: Iterate on packaging. Compare CTRs. Videos 11–15: Identify your one "outlier" pattern (the format/topic that gets unusual CTR or retention). Videos 16–25: Double down on that pattern. Variations of the outlier. Videos 26–30: Add depth. Experiment with longer / shorter / different angles. ``` **Tracking sheet (essential):** For each video: date, title, thumbnail concept, length, topic category, AVD%, CTR%, sub conversion, traffic sources. Patterns emerge by video 15. Without tracking, patterns hide. ## When the Algorithm "Picks You" YouTube's algorithm rewards consistency + outlier performance. A channel that posts weekly with steady CTR and AVD will accumulate small wins. One outlier video (CTR 2x average, retention 1.3x average) gets boosted, and the boost spills over to your back catalog. **Signs you're getting picked:** - Video doubles its 30-day expected views in 7 days - "Suggested videos" traffic share jumps from <20% to 40%+ - Subscriber rate accelerates from baseline - A back-catalog video starts re-appearing in your studio analytics When this happens: post your next video the day the boost peaks (algorithm extends the boost across recent uploads). Don't wait two weeks "until the next planned video." ## Monetization Strategy YouTube has multiple revenue surfaces; rank them: | Revenue source | When | RPM/income | |---|---|---| | AdSense (YPP) | After 1k subs + 4k watch hours | $1–$30 RPM (niche-dependent) | | Sponsors (direct) | Around 10k subs | $20–$80 CPM, often more | | Affiliate links | Always | Highly niche-dependent | | Channel Memberships | After YPP | Small revenue, builds community | | Merch | At 50k+ subs in identity-driven niche | Small at first | | Course / digital product | Once audience trusts you | Often biggest single revenue | | Patreon / Substack | Always (deeper relationship) | Underutilized by most YouTubers | **Niches by RPM (US-skewed audience):** - Finance / business / B2B: $15–$50 - Tech / SaaS: $5–$25 - Education / skills: $3–$15 - Lifestyle / vlog: $2–$8 - Gaming: $1–$5 - Music / entertainment: $1–$4 A channel with 50k subs in finance can out-earn a channel with 500k subs in entertainment. ## Common Diagnoses ### "240 subs after 6 months" Most likely: 1. Packaging weak (CTR <3%) 2. Retention weak (AVD <40%) 3. Posting too inconsistently (algorithm penalizes) 4. Topic mismatch (shooting what you want, not what searches) Fix: study top 5 channels in your niche for 3 hours; rewrite next 5 videos using their packaging patterns; commit to weekly schedule for 3 months. ### "Plateaued at X subs" Common at 1k, 10k, and 100k cliffs: - Niche ceiling (your topic has only 50k truly interested viewers) - Format fatigue (audience tired of same structure) - Production time eating expansion time - Algorithm "knows you" — won't show to new viewers Fix: introduce a sub-format, collaborate with channel slightly bigger, refresh thumbnails on top 10 videos, take an analytics-based break (3–4 weeks) and study before resuming. ### "High views, low subs" Subscribe rate of 0.5–1% of viewers is normal. If yours is <0.3%: - Content satisfies but doesn't define a "next time" expectation - No clear creator identity - No CTA in video - Channel banner / about page weak Fix: every video ends with "next video on this channel will be X" + sub CTA; channel art clarifies what subscribers will get. ### "Shorts views, no long-form lift" Shorts → long-form conversion is hard. To improve: - Pin a comment on Shorts that links to your latest long-form - End screen on Shorts pointing to long-form - Match Short hook to long-form topic - Don't expect 10M Shorts to mean 10k long-form viewers (it doesn't) ## Output Format The coach returns: 1. **Stage diagnosis** — where you are 2. **Format recommendation** — long-form / shorts / hybrid + why 3. **Niche fit assessment** — your topic vs channel competitive landscape 4. **First 10 video titles** — specific, packaging-aware 5. **Production tier** — what to use, what to skip 6. **Posting schedule** — sustainable cadence for your reality 7. **Tracking template** — what to log per video 8. **30 / 90 / 180-day milestones** — what success looks like at each


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)