fal-ai-media
affaan-m/ECC · Agent Skill
Generates images, videos, and audio using fal.ai models, including text-to-image, text-to-video, and text-to-speech.
Jump to install ↓Overview
| Publisher | |
|---|---|
| Repository | affaan-m/ECC ↗ |
| Skill folder | fal-ai-media |
| Stars | 257,549 |
| Forks | 38,524 |
| Bundled files | 2 |
| License | MIT |
| Last updated | September 12, 2026 |
| Links | Skill source ↗ · Repository ↗ |
Mozgi check
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Installation
A skill is a folder with a SKILL.md file. Pick your agent and run the commands in a terminal (macOS, Linux or Git Bash on Windows) from your project root.
Copy the prompt into Claude, Codex or another assistant: it will review the skill and install it for you.
Install the “fal-ai-media” skill from mozgi.io (https://mozgi.io/skills/fal-ai-media/) for me. 1. Download the archive: https://mozgi.io/skills/fal-ai-media/download If it fails, take the skill folder from the source: https://github.com/affaan-m/ECC/tree/main/.agents/skills/fal-ai-media 2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me. 3. Put the “fal-ai-media” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.). 4. Make sure <skills folder>/fal-ai-media/SKILL.md exists. 5. Briefly tell me what this skill does and offer to try it on my task. If you cannot do a step yourself, tell me what to click or type.
git clone --depth 1 --branch main https://github.com/affaan-m/ECC.git /tmp/ECC mkdir -p .claude/skills cp -r /tmp/ECC/.agents/skills/fal-ai-media .claude/skills/fal-ai-media
Restart Claude Code — the skill appears in the list; call it manually with /fal-ai-media. For all projects use ~/.claude/skills.
git clone --depth 1 --branch main https://github.com/affaan-m/ECC.git /tmp/ECC mkdir -p .agents/skills cp -r /tmp/ECC/.agents/skills/fal-ai-media .agents/skills/fal-ai-media
Codex looks for skills in .agents/skills from the current folder up to the repo root; call one with /skills or $fal-ai-media. For all projects use ~/.agents/skills.
git clone --depth 1 --branch main https://github.com/affaan-m/ECC.git /tmp/ECC mkdir -p .cursor/skills cp -r /tmp/ECC/.agents/skills/fal-ai-media .cursor/skills/fal-ai-media
Cursor picks the skill up on start; call it with “/” in Agent chat. Cursor also reads .claude/skills and .agents/skills. For all projects use ~/.cursor/skills.
git clone --depth 1 --branch main https://github.com/affaan-m/ECC.git /tmp/ECC mkdir -p .gemini/skills cp -r /tmp/ECC/.agents/skills/fal-ai-media .gemini/skills/fal-ai-media
Gemini CLI offers to activate the skill when a task matches — you approve it. For all projects use ~/.gemini/skills.
Read SKILL.md and any companion files before deciding whether to install. Click a file to preview it.
SKILL.md contents
Original author text · read-onlyfal.ai Media Generation
Generate images, videos, and audio using fal.ai models via MCP.
When to Activate
- User wants to generate images from text prompts
- Creating videos from text or images
- Generating speech, music, or sound effects
- Any media generation task
- User says "generate image", "create video", "text to speech", "make a thumbnail", or similar
MCP Requirement
fal.ai MCP server must be configured. Add to ~/.claude.json:
"fal-ai": {
"command": "npx",
"args": ["-y", "fal-ai-mcp-server"],
"env": { "FAL_KEY": "YOUR_FAL_KEY_HERE" }
}
Get an API key at fal.ai ↗.
MCP Tools
The fal.ai MCP provides these tools:
search— Find available models by keywordfind— Get model details and parametersgenerate— Run a model with parametersresult— Check async generation statusstatus— Check job statuscancel— Cancel a running jobestimate_cost— Estimate generation costmodels— List popular modelsupload— Upload files for use as inputs
---
Image Generation
Nano Banana 2 (Fast)
Best for: quick iterations, drafts, text-to-image, image editing.
generate(
model_name: "fal-ai/nano-banana-2",
input: {
"prompt": "a futuristic cityscape at sunset, cyberpunk style",
"image_size": "landscape_16_9",
"num_images": 1,
"seed": 42
}
)
Nano Banana Pro (High Fidelity)
Best for: production images, realism, typography, detailed prompts.
generate(
model_name: "fal-ai/nano-banana-pro",
input: {
"prompt": "professional product photo of wireless headphones on marble surface, studio lighting",
"image_size": "square",
"num_images": 1,
"guidance_scale": 7.5
}
)
Common Image Parameters
| Param | Type | Options | Notes |
|-------|------|---------|-------|
| prompt | string | required | Describe what you want |
| image_size | string | square, portrait_4_3, landscape_16_9, portrait_16_9, landscape_4_3 | Aspect ratio |
| num_images | number | 1-4 | How many to generate |
| seed | number | any integer | Reproducibility |
| guidance_scale | number | 1-20 | How closely to follow the prompt (higher = more literal) |
Image Editing
Use Nano Banana 2 with an input image for inpainting, outpainting, or style transfer:
# First upload the source image
upload(file_path: "/path/to/image.png")
# Then generate with image input
generate(
model_name: "fal-ai/nano-banana-2",
input: {
"prompt": "same scene but in watercolor style",
"image_url": "<uploaded_url>",
"image_size": "landscape_16_9"
}
)
---
Video Generation
Seedance 1.0 Pro (ByteDance)
Best for: text-to-video, image-to-video with high motion quality.
generate(
model_name: "fal-ai/seedance-1-0-pro",
input: {
"prompt": "a drone flyover of a mountain lake at golden hour, cinematic",
"duration": "5s",
"aspect_ratio": "16:9",
"seed": 42
}
)
Kling Video v3 Pro
Best for: text/image-to-video with native audio generation.
generate(
model_name: "fal-ai/kling-video/v3/pro",
input: {
"prompt": "ocean waves crashing on a rocky coast, dramatic clouds",
"duration": "5s",
"aspect_ratio": "16:9"
}
)
Veo 3 (Google DeepMind)
Best for: video with generated sound, high visual quality.
generate(
model_name: "fal-ai/veo-3",
input: {
"prompt": "a bustling Tokyo street market at night, neon signs, crowd noise",
"aspect_ratio": "16:9"
}
)
Image-to-Video
Start from an existing image:
generate(
model_name: "fal-ai/seedance-1-0-pro",
input: {
"prompt": "camera slowly zooms out, gentle wind moves the trees",
"image_url": "<uploaded_image_url>",
"duration": "5s"
}
)
Video Parameters
| Param | Type | Options | Notes |
|-------|------|---------|-------|
| prompt | string | required | Describe the video |
| duration | string | "5s", "10s" | Video length |
| aspect_ratio | string | "16:9", "9:16", "1:1" | Frame ratio |
| seed | number | any integer | Reproducibility |
| image_url | string | URL | Source image for image-to-video |
---
Audio Generation
CSM-1B (Conversational Speech)
Text-to-speech with natural, conversational quality.
generate(
model_name: "fal-ai/csm-1b",
input: {
"text": "Hello, welcome to the demo. Let me show you how this works.",
"speaker_id": 0
}
)
ThinkSound (Video-to-Audio)
Generate matching audio from video content.
generate(
model_name: "fal-ai/thinksound",
input: {
"video_url": "<video_url>",
"prompt": "ambient forest sounds with birds chirping"
}
)
ElevenLabs (via API, no MCP)
For professional voice synthesis, use ElevenLabs directly:
import os
import requests
resp = requests.post(
"https://api.elevenlabs.io/v1/text-to-speech/<voice_id>",
headers={
"xi-api-key": os.environ["ELEVENLABS_API_KEY"],
"Content-Type": "application/json"
},
json={
"text": "Your text here",
"model_id": "eleven_turbo_v2_5",
"voice_settings": {"stability": 0.5, "similarity_boost": 0.75}
}
)
with open("output.mp3", "wb") as f:
f.write(resp.content)
VideoDB Generative Audio
If VideoDB is configured, use its generative audio:
# Voice generation
audio = coll.generate_voice(text="Your narration here", voice="alloy")
# Music generation
music = coll.generate_music(prompt="upbeat electronic background music", duration=30)
# Sound effects
sfx = coll.generate_sound_effect(prompt="thunder crack followed by rain")
---
Cost Estimation
Before generating, check estimated cost:
estimate_cost(model_name: "fal-ai/nano-banana-pro", input: {...})
Model Discovery
Find models for specific tasks:
search(query: "text to video")
find(model_name: "fal-ai/seedance-1-0-pro")
models()
Tips
- Use
seedfor reproducible results when iterating on prompts - Start with lower-cost models (Nano Banana 2) for prompt iteration, then switch to Pro for finals
- For video, keep prompts descriptive but concise — focus on motion and scene
- Image-to-video produces more controlled results than pure text-to-video
- Check
estimate_costbefore running expensive video generations
Related Skills
videodb— Video processing, editing, and streamingvideo-editing— AI-powered video editing workflowscontent-engine— Content creation for social platforms
Frequently asked questions
What does the fal-ai-media skill do?
Generates images, videos, and audio using fal.ai models, including text-to-image, text-to-video, and text-to-speech.
How do I install fal-ai-media?
Open the “Installation” block on this page and pick your agent — Claude Code, Codex, Cursor or Gemini CLI — for ready-made commands that copy the skill folder to the right place. Or copy the prompt from the “Via assistant” tab and let the assistant review and install the skill.
Which AI models work with fal-ai-media?
Skills are plain Markdown instructions (the Agent Skills format), so fal-ai-media works with any agent that reads SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and more. The model loads the instructions only when a task matches the skill's description.
Is fal-ai-media free?
The skill is published openly by affaan-m under the MIT license. The skill itself costs nothing — you only pay your AI provider for the tokens you use.
Is it safe to install skills?
A skill is a set of instructions your agent will follow, so read SKILL.md and its companion files before installing. Scripts in the skill folder only run if your agent runs them — keep an eye on what it does and do not grant unnecessary permissions.
How is a skill different from an MCP server or a plugin?
An MCP server or plugin gives the model new tools — code that runs and returns a result. A skill gives it knowledge and process: how to approach a task, which steps to follow and what good output looks like. It needs no server or API key.