fal

name	fal
version	1.0.1
description	Search, explore, and run fal.ai generative AI models (image generation, video, audio, 3D). Use when user wants to generate images, videos, or other media with AI models.
allowed-tools	Bash(curl *), Bash(jq *), Bash(mkdir *), Read, Write
argument-hint	<command> [model_id] [--param value]

fal.ai Model API Skill

Run 1000+ generative AI models on fal.ai.

Arguments

• Command: $0 (search | schema | run | status | result | upload)
• Arg 1: $1 (model_id, search query, or file path)
• Arg 2+: $2, $3, etc. (additional parameters)
• All args: $ARGUMENTS

Session Output

Save generated files to session folder:

mkdir -p ~/.fal/sessions/${CLAUDE_SESSION_ID}

Downloaded images/videos go to: ~/.fal/sessions/${CLAUDE_SESSION_ID}/

---

Authentication

Requires FAL_KEY environment variable. If requests fail with 401, tell user:

Get an API key from https://fal.ai/dashboard/keys
Then: export FAL_KEY="your-key-here"

---

Command: $0

If $0 = "search"

Search for models matching $1:

curl -s "https://api.fal.ai/v1/models?q=$1&limit=15" \
  -H "Authorization: Key $FAL_KEY" | jq -r '.models[] | "• \(.endpoint_id) — \(.metadata.display_name) [\(.metadata.category)]"'

For category search, use:

curl -s "https://api.fal.ai/v1/models?category=$1&limit=15" \
  -H "Authorization: Key $FAL_KEY" | jq -r '.models[] | "• \(.endpoint_id) — \(.metadata.display_name)"'

Categories: text-to-image, image-to-video, text-to-video, image-to-3d, training, speech-to-text, text-to-speech

---

If $0 = "schema"

Get input schema for model $1:

curl -s "https://api.fal.ai/v1/models?endpoint_id=$1&expand=openapi-3.0" \
  -H "Authorization: Key $FAL_KEY" | jq '.models[0].openapi.components.schemas.Input.properties'

Show required vs optional fields to help user understand what inputs are needed.

---

If $0 = "run"

Run model $1 with parameters from remaining arguments.

Step 1: Parse parameters Extract --key value pairs from $ARGUMENTS after the model_id to build JSON payload.

Example: /fal run fal-ai/flux-2 --prompt "a cat" --image_size landscape_16_9 → Model: fal-ai/flux-2 → Payload: {"prompt": "a cat", "image_size": "landscape_16_9"}

Step 2: Submit to queue

curl -s -X POST "https://queue.fal.run/$1" \
  -H "Authorization: Key $FAL_KEY" \
  -H "Content-Type: application/json" \
  -d '<JSON_PAYLOAD>'

Step 3: Poll until complete

# Get request_id from response, then poll:
while true; do
  STATUS=$(curl -s "https://queue.fal.run/$1/requests/$REQUEST_ID/status" \
    -H "Authorization: Key $FAL_KEY" | jq -r '.status')
  echo "Status: $STATUS"
  if [ "$STATUS" = "COMPLETED" ]; then break; fi
  if [ "$STATUS" = "FAILED" ]; then echo "Job failed"; break; fi
  sleep 3
done

Step 4: Get result and save

# Fetch result
RESULT=$(curl -s "https://queue.fal.run/$1/requests/$REQUEST_ID" \
  -H "Authorization: Key $FAL_KEY")

# Create session output folder
mkdir -p ~/.fal/sessions/${CLAUDE_SESSION_ID}

# Download images/videos
# For images: jq -r '.images[0].url' and curl to download
# Save as: ~/.fal/sessions/${CLAUDE_SESSION_ID}/<timestamp>_<model>.png

---

If $0 = "status"

Check status of request $2 for model $1:

curl -s "https://queue.fal.run/$1/requests/$2/status?logs=1" \
  -H "Authorization: Key $FAL_KEY" | jq '{status: .status, queue_position: .queue_position, logs: .logs}'

---

If $0 = "result"

Get result of completed request $2 for model $1:

curl -s "https://queue.fal.run/$1/requests/$2" \
  -H "Authorization: Key $FAL_KEY" | jq '.'

---

If $0 = "upload"

Upload file $1 to fal CDN:

curl -s -X POST "https://fal.run/fal-ai/storage/upload" \
  -H "Authorization: Key $FAL_KEY" \
  -F "file=@$1"

Returns URL to use in model requests.

---

Quick Reference

Popular models:

• fal-ai/flux-2 — Fast text-to-image
• fal-ai/flux-2-pro — High quality text-to-image
• fal-ai/kling-video/v2/image-to-video — Image to video
• fal-ai/minimax/video-01/image-to-video — Image to video
• fal-ai/whisper — Speech to text

Common parameters for text-to-image:

• --prompt "description" — What to generate
• --image_size landscape_16_9 — Aspect ratio (square, portrait_4_3, landscape_16_9)
• --num_images 1 — Number of images

Example invocations:

• /fal search video — Find video models
• /fal schema fal-ai/flux-2 — See input options
• /fal run fal-ai/flux-2 --prompt "a sunset over mountains"
• /fal status fal-ai/flux-2 abc-123
• /fal upload ./photo.png