About fal-prompting
fal-prompting is a reference skill for writing prompts tailored to fal.ai model families. It combines general visual prompting advice with model-specific guidance for Kling, GPT Image 2, and Happy Horse.
Key features
- 01Model-family-specific prompting guides
- 02Visual detail over prestige adjectives
- 03Style guidance with concrete targets
- 04Controlled single-variable iterations
- 05Schema checks for available controls
Use cases
- 01Write prompts for Kling video models
- 02Prepare structured GPT Image 2 prompts
- 03Adapt prompts for Happy Horse
- 04Refine visual output one variable at a time
Install
Copy the command and run it in a terminal.
npx skills add https:/After installing, type/fal-promptingin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
references/gpt-image-2.mdhappy-horse.mdkling.mdDetails
From the project READMEfal.ai Prompting
Runtime: All endpoint calls run via the genmedia CLI. See the
genmediaskill for command syntax; rungenmedia initonce if not yet installed.
Model families have meaningful prompting nuances. A prompt that works on GPT Image 2 (long, structured, exact text in quotes) will fail on Happy Horse (which wants ~20 plain-English words). This skill collects family-specific guides.
When to load which reference
| Reference | Load when |
|---|---|
| kling.md | Working with Kling video models (O3, v3), multi-prompt, element controls, Standard vs Pro tier |
| gpt-image-2.md | Working with openai/gpt-image-2 or /edit, structured prompts, EXACT TEXT, multi-image compositing |
| happy-horse.md | Working with alibaba/happy-horse/text-to-video or image-to-video, brevity-first, camera language |
Universal principles (all families)
- Visual facts beat prestige adjectives. Replace "stunning, cinematic, masterpiece" with "overcast daylight, brushed aluminum, 50mm feel."
- Style tags need visual targets. "Minimalist brutalist" → "cream background, heavy black sans serif, asymmetrical type block, generous negative space."
- One controlled variable per iteration. Comparison only works when one axis changes at a time.
- Inspect schema before assuming a control exists.
genmedia schema <endpoint_id> --json. Negative prompt, seed, multi-prompt, and reference-image fields differ across families. - Per-family rules override universal advice. Happy Horse rejects what GPT Image 2 rewards.
Catalog cross-reference
For "which model do I use" questions, see fal-models-catalog:
- Text-to-image endpoint selection → fal-models-catalog/references/text-to-image.md
- Text-to-video endpoint selection → fal-models-catalog/references/text-to-video.md
- Image-to-video endpoint selection → fal-models-catalog/references/image-to-video.md