research-music-trends

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Research the current music landscape — genres growing, viral patterns, breakout artist profiles, platform dynamics, and AI music feasibility. Use this skill whenever starting Phase 1 of the AI artist factory, when you need to understand what music is trending, which genres are emerging, what sounds Suno can produce convincingly, or when the manager skill requests a music landscape update.

fltman By fltman schedule Updated 3/2/2026

name: research-music-trends description: Research the current music landscape — genres growing, viral patterns, breakout artist profiles, platform dynamics, and AI music feasibility. Use this skill whenever starting Phase 1 of the AI artist factory, when you need to understand what music is trending, which genres are emerging, what sounds Suno can produce convincingly, or when the manager skill requests a music landscape update. allowed-tools: WebSearch, WebFetch, Read, Write, Bash

Music Trends Research

Research the current music landscape to find where the momentum is. Data-driven, not opinionated. Use web search for ALL claims — never rely on training data for trends.

Research Areas

  1. Genre momentum — Growth on Spotify/Apple/SoundCloud/YouTube. Emerging vs peaking vs declining. Micro-genres bubbling up. Passionate fanbases with low competition.
  2. Viral patterns — What songs/artists went viral recently and WHY. Common breakout traits. Niche-to-mainstream crossover profile.
  3. Platform dynamics — Where discovery happens (TikTok, Spotify Discover, YouTube Shorts). Which platforms reward new artists. Best song lengths/structures per platform.
  4. Artist archetypes — Personas resonating now. Solo vs band vs anonymous. Role of backstory.
  5. AI music landscape — Existing AI music projects. Audience reception. Platform policies. Detection risks.
  6. Suno feasibility — What genres Suno produces convincingly. Where AI sounds most/least authentic. Forgiving genres.

Method

  1. Search current Spotify/Apple Music trend reports
  2. Search "breakout artists 2025/2026", "music trends 2026"
  3. Search genre-specific growth data
  4. Search TikTok music trends, viral sounds
  5. Search AI music reception and Suno capabilities
  6. Cross-reference multiple sources

Output

Save to outputs/research/music-trends-[date].md:

# Music Trends Report — [Date]

## Executive Summary
[3-5 sentences: key takeaway for concept decision]

## Growing Genres (ranked by opportunity)
### 1. [Genre]
- Growth signals: [data]
- Audience & demo: [who]
- Competition: [crowded?]
- AI feasibility: [Suno quality]
- Viral potential: [shareability]
- Verdict: [strong/moderate/weak]

## Breakout Artist Patterns
[Common traits]

## Platform Opportunities
[Where a new unknown artist has the best shot]

## AI Feasibility Matrix
| Genre | Suno Quality | Auth. Risk | Competition | Rec. |
|-------|-------------|------------|-------------|------|

## Key Insight
[Single most important finding]
Install via CLI
npx skills add https://github.com/fltman/ai-artist-factory --skill research-music-trends
Repository Details
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call_split Forks 1
navigation Branch main
article Path SKILL.md
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