tiktok-slideshow

name	tiktok-slideshow
description	Orchestrator skill that chains /slideshow-script → /paper-marketing → /video-content for end-to-end TikTok slideshow production. Each phase is an independent Lego block — this orchestrator is just one recipe that combines them. Produces 5 publishable TikTok videos from a single positioning angle. Triggers on "TikTok slideshow", "TikTok video", "make TikTok", "slideshow video", "TikTok content".
allowed-tools	["Bash(mktg status *)","Bash(ffmpeg *)","Bash(bun *)","Bash(bunx remotion *)"]

/tiktok-slideshow — End-to-End TikTok Content Pipeline

Orchestrator that chains 3 atomic skills into a complete TikTok production pipeline:

/slideshow-script  →  /paper-marketing  →  /video-content
   (5 scripts)         (5 designs)          (5 videos)

Each skill is a Lego block that works independently. This orchestrator is one recipe.

Architecture

Phase 1: SCRIPT  — /slideshow-script generates 5 narrative scripts
Phase 2: DESIGN  — /paper-marketing creates 5 visual designs (1 per script)
Phase 3: VIDEO   — /video-content assembles videos from designs

Platform spec: TikTok 1080×1920, 9:16, 30fps, H.264

Prerequisites

Before starting, verify all 3 sub-skills are installed:

• ~/.claude/skills/slideshow-script/SKILL.md
• ~/.claude/skills/paper-marketing/SKILL.md
• ~/.claude/skills/video-content/SKILL.md

If any sub-skill is missing, tell the user and recommend mktg update to install it. Do not proceed without all 3.

Workflow

Phase 1: SCRIPT

Load the /slideshow-script skill at ~/.claude/skills/slideshow-script/SKILL.md and follow its workflow:

1. Read brand files (positioning, audience, voice)
2. User selects positioning angle
3. Generate up to 5 scripts using 5 storytelling frameworks (AIDA, PAS, BAB, Star-Story-Solution, Stat-Flip). User may select fewer at the gate.
4. Each script uses the brand voice from brand/voice-profile.md for tone, vocabulary, and signature phrases
5. Present all 5 scripts for approval
6. Write 5 content spec YAMLs to marketing/content-specs/

Gate: User must approve scripts before Phase 2.

Phase 2: DESIGN

Load the /paper-marketing skill at ~/.claude/skills/paper-marketing/SKILL.md and follow its workflow, with these orchestrator-specific instructions:

1. Paper-marketing Phase 1 (Load Brand) proceeds as normal
2. Skip Phase 2a-2d — the content specs already exist from Phase 1
3. Instead, read the 5 content spec YAMLs from marketing/content-specs/
4. Each content spec has a visual_direction field — use that to set each agent's design brief
5. Each agent gets its content spec's unique script (different slides, different narrative)
6. Each agent loads the /frontend-design skill for design quality
7. Spawn agents — number depends on how many scripts the user approved (could be 3-5)

Script-to-design mapping from content specs:

Content Spec	Visual Direction	Framework
{project}-aida.yaml	typographic	AIDA
{project}-pas.yaml	contrast-play	PAS
{project}-bab.yaml	atmospheric	BAB
{project}-story.yaml	editorial	Star-Story-Solution
{project}-statflip.yaml	data-led	Stat-Flip

8. User reviews all designs, selects favorite(s)
9. Extract get_jsx() from selected artboard(s)
10. Write handoff YAML(s) to marketing/handoffs/

Gate: User must select variation(s) and export PNG from Paper UI.

Phase 3: VIDEO

Load the /video-content skill at ~/.claude/skills/video-content/SKILL.md and follow its workflow:

1. Detect handoff YAML from Phase 2
2. ffmpeg slice the exported PNG into individual slides
3. User selects tier (v1 Quick / v1.5 Enhanced / v2 Full)
4. Assemble video at chosen tier
5. ffmpeg post-process (thumbnail, GIF preview, platform encode)

For multiple selections: If user approved multiple designs, run video assembly for each. Can be parallelized — each video is independent.

Gate: User approves final video(s).

Human-in-the-Loop Gates

[Phase 1] → User approves 5 scripts
[Phase 2] → User selects design variation(s), exports PNG(s) from Paper UI
[Phase 3] → User selects video tier, approves final output

Each gate is an AskUserQuestion. The user can go back to any phase.

Output

marketing/content-specs/
  {project}-aida.yaml
  {project}-pas.yaml
  {project}-bab.yaml
  {project}-story.yaml
  {project}-statflip.yaml

marketing/handoffs/
  {project}-{variation}-handoff.yaml

marketing/video/
  {project}-{variation}/
    slides/
    output_{tier}.mp4
    thumbnail.png
    preview.gif

Reusable Blocks

Each skill in this chain works independently:

Block	Standalone Use
/slideshow-script	Generate scripts for any format (Instagram carousel, YouTube, email)
/paper-marketing	Design any visual content (not just slideshows)
/video-content	Assemble video from any PNGs (not just Paper exports)

Other Orchestrator Recipes (Future)

Same blocks, different combinations:

/instagram-carousel  = /slideshow-script → /paper-marketing (4:5 ratio, no video)
/youtube-short       = /slideshow-script → /paper-marketing → /video-content (16:9)
/reels-batch         = /slideshow-script (10 scripts) → /paper-marketing → /video-content × 10
/ad-creative         = /slideshow-script (1 script) → /paper-marketing (1 slide) → /video-content

Error Recovery

Failure	Action
Sub-skill not installed	Stop, recommend mktg update, do not proceed
Phase 1 scripts rejected	Revise scripts with user feedback, do not advance to Phase 2
Paper MCP unavailable	Fall back to manual slide creation; user provides PNGs
Phase 2 design export fails	User re-exports from Paper UI; agent retries video assembly
Phase 3 video assembly fails	Check ffmpeg/Remotion installation, retry with v1 tier first

Anti-Patterns

Anti-Pattern	Instead
Skipping human gates between phases	Always wait for user approval at each gate
Running all 3 phases without stopping	Each phase has an explicit gate — never auto-advance
Generating all 5 when user only wants 2	Respect user selection at Phase 1 gate
Re-using the same visual direction for all designs	Each content spec maps to a unique visual direction
Loading sub-skills via Bash instead of reading SKILL.md	Load each skill's SKILL.md and follow its instructions

Principles

• Skills never call skills — this SKILL.md teaches the agent the sequence; the agent loads each skill
• Filesystem is the bus — content specs and handoffs are YAML files, not API calls
• Human gates at every phase — no runaway agent chains
• Progressive quality — start with v1 to verify, upgrade to v2 for production
• All outputs are publishable — different scripts, different designs, not N versions of 1