viral-launch-pipeline

viral-launch-pipeline

A Claude Code plugin that replicates the 21-agent viral product launch pipeline used by some of the largest X launches. One orchestrator skill (viral-launch) coordinates 21 specialized subagents — research, hook writing, manager critique, weapons/controversy/technical/flow specialists, Mom Test, multi-channel delivery — to produce an X-thread + LinkedIn post + ProductHunt copy from a single user prompt.

The pipeline forces every piece of the launch to get attacked, rewritten, scored, and improved before it reaches the final version. This is the difference between AI-written launch copy that goes nowhere and copy that earns attention.

What it produces

From one prompt (e.g. viral launch for Cursor 2.0), the skill writes:

• X-thread — 7-12 tweets (hook + body + giveaway + CTA), each within X's 280-char limit
• LinkedIn post — single 900-1,300 char post using a 2026 hook formula
• ProductHunt — tagline + description + maker's first comment + topics + gallery brief

Plus a full paper trail in launches/<slug>/: research notes, hook iterations, manager critiques, body specialist transformations, Mom Test report, and supervisor coherence checks.

Installation

# In Claude Code:
/plugin marketplace add Koz-TV/viral-launch-pipeline
/plugin install viral-launch-pipeline@viral-launch-pipeline

Restart your Claude Code session. The viral-launch skill is now available.

For local development against the source tree:

/plugin marketplace add ~/Documents/Projects/skills-maker/viral-launch-pipeline
/plugin install viral-launch-pipeline@viral-launch-pipeline

Usage

Start a launch

In any directory (the skill writes artifacts to ./launches/<slug>/ relative to CWD):

viral launch for {Product Name}

The skill will:

1. Ask you for the brand-brief facts it needs (product details, ICP, founder voice, etc.)
2. Run 4 research agents in parallel (YouTube, X/Twitter, Reddit, Industry)
3. Compile novelty angles
4. Write 5 hook candidates, critique them, iterate (max 3 times)
5. Design a giveaway, critique it, iterate
6. Mid-pipeline coherence check (Call Supervisor)
7. Write the body, run 4 specialists (weapons / controversy / technical / flow), critique it, iterate
8. Run the Mom Test — flag jargon, kick back to body writer if too much (max 1 kickback)
9. Late-pipeline coherence check
10. Final polish
11. Adapt to X / LinkedIn / ProductHunt formats

You'll get short status updates at every major checkpoint. Total wall time: ~30-60 minutes depending on research breadth.

Resume a launch

resume the launch for {Product Name}

The skill reads ./launches/<slug>/meta.json and picks up exactly where it left off, including mid-loop iteration counters.

Architecture

• One orchestrator skill (skills/viral-launch/SKILL.md) drives the pipeline
• 21 stage prompts (skills/viral-launch/prompts/01_*.md … 21_*.md), each self-contained
• 6 reference docs (skills/viral-launch/references/):
  • orchestrator-protocol.md — dispatch wrapper + dependency map
  • artifact-schema.md — directory layout + meta.json schema
  • rubric-format.md — manager critique JSON schema
  • search-query-templates.md — queries for research stages
  • channel-specs.md — X/LinkedIn/PH format specs
  • hook-three-question-test.md — the hook QA test

The orchestrator runs every stage via Agent(subagent_type="general-purpose", prompt=<wrapper>). Each subagent reads its dependencies from launches/<slug>/, writes its output back to the same directory, and returns a short summary. Main Claude updates meta.json after each stage — that's the resumability mechanism.

The 21 stages

1.  Brand Brief         → 2.  Keywords      → [PARALLEL: 3-6 research] → 7.  Research Compiler
8.  Hook Writer       ↔ 9.  Hook Manager (max 3 iter)
10. Giveaway Writer   ↔ 11. Giveaway Manager (max 3 iter)
19. Call Supervisor (mid)  ← coherence check between hook + giveaway
12. Body Writer       → 13. Weapons → 14. Controversy → 15. Technical → 16. Flow → 17. Body Manager (max 3 iter)
18. Mom Test         (kicks back to 12 once if ≥3 jargon flags)
19. Call Supervisor (late) ← coherence check between hook + giveaway + body
20. Final Review
21. Deliver           → x_thread.md + linkedin_post.md + producthunt.md

Why this works

Most AI-written launches are average because the AI writes the launch in one pass. This pipeline: