fal-ai

name: fal-ai description: This skill enables AI video generation from images AND text-to-speech voiceover generation using Fal.ai's API. Use this skill when the user asks to (1) generate videos from images (image-to-video), or (2) generate voiceovers/narration from text (text-to-speech via ElevenLabs). Works seamlessly with the nano-banana skill for image-to-video workflows. IMPORTANT: Check references/ for latest models and pricing - AI models change frequently.

Fal.ai Media Generation

Generate AI videos from images and AI voiceovers from text using Fal.ai's API.

Capabilities:

• Image-to-Video: Generate video clips from static images (see below)
• Text-to-Speech: Generate voiceovers using ElevenLabs voices (see TTS section)

Prerequisites

This skill requires a FAL_API_KEY in the project's .env or .env.local file:

FAL_API_KEY=your_api_key_here

To obtain an API key, visit: https://fal.ai/dashboard/keys

Primary Capability: Image-to-Video

Generate video clips from static images using scripts/image_to_video.py:

python scripts/image_to_video.py image.png \
  --prompt "camera slowly pans right, gentle motion"

Parameters:

• image (required): Path to input image or URL
• --prompt, -p: Motion/action description for the video
• --model, -m: Video model to use (default: kling)
• --output, -o: Output directory or file path (default: current directory)
• --duration, -d: Video duration in seconds (model-dependent, typically 5-10)

Model Selection Strategy

Video generation is expensive. Follow this workflow:

1. Iterate with cheap models (Wan/Kling) - Perfect your prompts at $0.05-0.07/sec
2. Test with Veo Fast - Verify quality improvement at $0.15/sec
3. Final render with Veo Standard - Premium output at $0.40/sec

Quick Model Reference (January 2026)

For detailed model comparison, strengths/weaknesses, and latest updates, see references/api_reference.md.

Usage Examples

Basic video generation (default Kling model):

python scripts/image_to_video.py photo.png \
  --prompt "gentle breeze moves the leaves, soft lighting"

Budget iteration with Wan:

python scripts/image_to_video.py photo.png \
  --prompt "camera zooms in slowly" \
  --model wan

Premium render with Veo:

python scripts/image_to_video.py photo.png \
  --prompt "cinematic dolly shot, dramatic lighting" \
  --model veo \
  --output final_video.mp4

Specify duration:

python scripts/image_to_video.py photo.png \
  --prompt "waves crash on the shore" \
  --duration 10

Workflow with Nano Banana

Generate an image, then create a video from it:

# Step 1: Generate image with Nano Banana
python .claude/skills/nano-banana/scripts/generate_image.py \
  "a serene Japanese garden with cherry blossoms" \
  --output garden.png

# Step 2: Iterate with Kling (default, $0.35 for 5 sec)
python skills/fal-ai/scripts/image_to_video.py \
  garden.png \
  --prompt "gentle breeze moves cherry blossom petals, camera slowly pans right"

# Step 3: Final render with Veo when satisfied ($2.00 for 5 sec)
python skills/fal-ai/scripts/image_to_video.py \
  garden.png \
  --prompt "gentle breeze moves cherry blossom petals, camera slowly pans right" \
  --model veo

Text-to-Speech Voiceovers

Generate AI voiceovers using ElevenLabs voices via scripts/text_to_speech.py:

python scripts/text_to_speech.py "Your text here" --voice george

Parameters:

• text (required): Text to convert to speech
• --voice, -v: Voice name (see casting guide below)
• --model, -m: TTS model (default: eleven-v3)
• --output, -o: Output directory or file path
• --stability: Emotion control 0-1 (lower = more emotion)
• --similarity: Voice matching 0-1
• --style: Expression exaggeration 0-1
• --speed: Speaking pace 0.7-1.2
• --list-voices: Show all available voices

TTS Model Reference (January 2026)

Voice Casting Quick Reference

When the user describes what they're looking for, match to these voices:

Female Voices:

Male Voices:

For full casting descriptions and parameter presets, see references/tts_reference.md.

TTS Usage Examples

Basic voiceover:

python scripts/text_to_speech.py "Welcome to our product demo." --voice george

Voice casting (run multiple to compare):

TEXT="Introducing the future of productivity."
python scripts/text_to_speech.py "$TEXT" --voice george -o casting_george.mp3
python scripts/text_to_speech.py "$TEXT" --voice eric -o casting_eric.mp3
python scripts/text_to_speech.py "$TEXT" --voice chris -o casting_chris.mp3

Documentary style (authoritative, slower):

python scripts/text_to_speech.py "In the depths of the ocean..." \
  --voice george --stability 0.65 --speed 0.95

Conversational style (more emotion):

python scripts/text_to_speech.py "Hey, check this out!" \
  --voice aria --stability 0.4 --style 0.3

With audio tags (eleven-v3 only):

python scripts/text_to_speech.py "[whispers] This is a secret..." --voice rachel

Resources

scripts/

• image_to_video.py - Image-to-video generation script
• text_to_speech.py - Text-to-speech voiceover script
• requirements.txt - Python dependencies (install with pip install -r requirements.txt)

references/

• api_reference.md - Video model comparison, pricing, best practices
• tts_reference.md - Voice casting guide, parameter presets, TTS best practices

Notes

• Models evolve rapidly: Check reference docs dates. If >1 month old, research latest models on Fal.ai before generating
• Video is expensive: Always be aware of costs. Iterate cheap, render expensive.
• TTS is cheap: Run voice casting calls (~$0.02 for 3 samples) before committing to full narration
• Queue-based API: Generation takes time. Scripts show progress updates.
• Output formats: Videos = MP4, Audio = MP3
• Duration limits: Video models typically support 5-10 seconds. Check api_reference.md.