happy-horse-video-workflow-architect
/install 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
- Docs: https://happy-horse.pro/docs/happy-horse-video-workflow-architect
- Demo: https://happy-horse.pro/ai-video-generator
- Create: https://happy-horse.pro/create
- Pricing: https://happy-horse.pro/pricing
- Raw SKILL.md: https://happy-horse.pro/skills/happy-horse-video-workflow-architect/SKILL.md
- Product guide: https://happy-horse.pro/blog/what-is-happy-horse
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
- Identify the core use case:
- prompt-to-video ideation
- image-to-video animation
- reference-driven video
- short-form campaign testing
- Extract the essentials:
- goal
- subject
- motion
- camera behavior
- reference inputs
- style and lighting
- success criteria
- 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.
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install happy-horse-video-workflow-architect - After installation, invoke the skill by name or use
/happy-horse-video-workflow-architect - Provide required inputs per the skill's parameter spec and get structured output
What is happy-horse-video-workflow-architect?
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-... It is an AI Agent Skill for Claude Code / OpenClaw, with 129 downloads so far.
How do I install happy-horse-video-workflow-architect?
Run "/install happy-horse-video-workflow-architect" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is happy-horse-video-workflow-architect free?
Yes, happy-horse-video-workflow-architect is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does happy-horse-video-workflow-architect support?
happy-horse-video-workflow-architect is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created happy-horse-video-workflow-architect?
It is built and maintained by happyhorse (@huangchen0); the current version is v1.0.0.