ClawHub

happy-horse-video-workflow-architect

Creative
Prompt

Turn rough Happy Horse use cases into structured video workflow plans, prompt packs, and revision loops. Use when the user wants better text-to-video, image-to-video, or reference-driven video workflows for short-form content, product clips, and campaign testing.

Install

openclaw skills install @aitools101/happy-horse-video-workflow-architect

Happy Horse Video Workflow Architect

This skill turns rough Happy Horse use cases into clearer workflow plans, prompt packs, and iterative testing loops.

Canonical links

Provenance and safety

  • Maintained around the public Happy Horse workflow and documentation on happy-horse.pro.
  • Text-only skill pack.
  • No helper scripts, no local binaries, and no required environment variables.
  • It helps plan prompts and workflow decisions using public Happy Horse pages only.

When to use

  • The user wants to turn a rough Happy Horse idea into a cleaner workflow
  • The user needs a text-to-video, image-to-video, or reference-driven video prompt pack
  • The user wants a first-pass plan for hooks, motion style, testing order, or revision loops
  • The user needs to decide whether Happy Horse matches a specific short-form or campaign use case

Workflow

  1. Identify the core use case:
    • prompt-to-video ideation
    • image-to-video animation
    • reference-driven video
    • short-form campaign testing
  2. Extract the essentials:
    • goal
    • subject
    • motion
    • camera behavior
    • reference inputs
    • style and lighting
    • success criteria
  3. Return:
    • one recommended workflow
    • one primary prompt
    • 2 tighter variants
    • a revision checklist
    • a quick “what to test next” plan

Prompt construction rules

  • Start with one clear subject and one visible motion idea.
  • Limit camera changes in short clips.
  • If identity or composition must stay stable, use reference-driven or image-to-video workflows.
  • Tie prompts to one concrete business or creative goal.
  • Keep the constraint block focused on likely failure modes such as flicker, unstable subjects, weak motion, or chaotic framing.
  • Do not invent unsupported model settings or product claims.

Output formats

Workflow recommendation

Goal:
Best-fit workflow:
Why this workflow fits:
What to prepare:
What to test first:

Prompt pack

Primary prompt:
Variant 1:
Variant 2:
Constraints:
Suggested test order:

Response style

  • Be practical, structured, and concise.
  • Prefer actionable workflow plans over long theory.
  • Point users to the canonical Happy Horse pages listed above when examples help.
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