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fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

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fal.ai Media Generation

Drift-prone skill. fal.ai model IDs, pricing, inputs, and MCP tool names change quickly. Search or fetch the current model metadata before promising a specific model, parameter, output format, or cost.

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 keyword
  • find — Get model details and parameters
  • generate — Run a model with parameters
  • result — Check async generation status
  • status — Check job status
  • cancel — Cancel a running job
  • estimate_cost — Estimate generation cost
  • models — List popular models
  • upload — Upload files for use as inputs

Image Generation

Nano Banana 2 (Fast)

Best for: quick iterations, drafts, text-to-image, image editing.

generate(
  app_id: "fal-ai/nano-banana-2",
  input_data: {
    "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(
  app_id: "fal-ai/nano-banana-pro",
  input_data: {
    "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

ParamTypeOptionsNotes
promptstringrequiredDescribe what you want
image_sizestringsquare, portrait_4_3, landscape_16_9, portrait_16_9, landscape_4_3Aspect ratio
num_imagesnumber1-4How many to generate
seednumberany integerReproducibility
guidance_scalenumber1-20How 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(
  app_id: "fal-ai/nano-banana-2",
  input_data: {
    "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(
  app_id: "fal-ai/seedance-1-0-pro",
  input_data: {
    "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(
  app_id: "fal-ai/kling-video/v3/pro",
  input_data: {
    "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(
  app_id: "fal-ai/veo-3",
  input_data: {
    "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(
  app_id: "fal-ai/seedance-1-0-pro",
  input_data: {
    "prompt": "camera slowly zooms out, gentle wind moves the trees",
    "image_url": "<uploaded_image_url>",
    "duration": "5s"
  }
)

Video Parameters

ParamTypeOptionsNotes
promptstringrequiredDescribe the video
durationstring"5s", "10s"Video length
aspect_ratiostring"16:9", "9:16", "1:1"Frame ratio
seednumberany integerReproducibility
image_urlstringURLSource image for image-to-video

Audio Generation

CSM-1B (Conversational Speech)

Text-to-speech with natural, conversational quality.

generate(
  app_id: "fal-ai/csm-1b",
  input_data: {
    "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(
  app_id: "fal-ai/thinksound",
  input_data: {
    "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(
  estimate_type: "unit_price",
  endpoints: {
    "fal-ai/nano-banana-pro": {
      "unit_quantity": 1
    }
  }
)

Model Discovery

Find models for specific tasks:

search(query: "text to video")
find(endpoint_ids: ["fal-ai/seedance-1-0-pro"])
models()

Tips

  • Use seed for 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_cost before running expensive video generations

Related Skills

  • videodb — Video processing, editing, and streaming
  • video-editing — AI-powered video editing workflows
  • content-engine — Content creation for social platforms

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA standards. Use this skill to generate semantic ARIA for Web and accessibility traits for Web and Native platforms (iOS/Android).

日本語の概要は準備中です。原文の説明を表示しています。

tensology/decisionsai172026年10月10日 更新

Whole site or product — a full web accessibility (a11y) audit against WCAG 2.2, following the WCAG-EM methodology. Defines scope, samples representative pages and flows, runs the automated tier (`accessibility-scan`) and the hands-on manual tier (`accessibility-inspect`), and produces one conformance report. Grades each finding by severity and evidence basis, and states per-criterion conformance as pass, fail, or undetermined (needs a human). Use it for 'audit my site for accessibility', 'is this product accessible', 'a11y audit', 'WCAG or Section 508 conformance report', or any multi-page assessment. Assesses; does not fix (use `accessibility-fix`) or diff (use `accessibility-diff`). For a single page use `accessibility-scan`; for hands-on keyboard and screen-reader checks use `accessibility-inspect`.

日本語の概要は準備中です。原文の説明を表示しています。

tensology/decisionsai172026年10月10日 更新

Regression check — diff a live page's web accessibility (a11y) violations against a baseline. By default it compares your uncommitted changes (stash-based); pass `--branch [<name>]` to compare against a branch. Reports the new WCAG violations introduced, the ones fixed, and the count of pre-existing ones. Use it for 'did my change break accessibility', 'what a11y issues did this PR add', or as a CI gate. For a full scan of one page use `accessibility-scan`; for a whole site use `accessibility-audit`.

日本語の概要は準備中です。原文の説明を表示しています。

tensology/decisionsai172026年10月10日 更新

Remediation only — repair web accessibility (a11y) violations against WCAG 2.2 with a baseline, edit, and verify loop. Takes a target (URL, files, directory) or a findings worklist from `accessibility-scan`/`accessibility-inspect`/`accessibility-audit`, applies mechanical fixes as given, leaves TODOs for visual or contextual judgment, and verifies by re-running the baseline check. It only fixes. To find issues use `accessibility-scan` (one page, automated), `accessibility-inspect` (one page, manual), or `accessibility-audit` (whole site, WCAG-EM); to check for regressions use `accessibility-diff`. Use it for 'fix the a11y issues in X', 'make this accessible', 'add missing alt text and labels', 'apply these accessibility fixes', 'remediate these violations'.

日本語の概要は準備中です。原文の説明を表示しています。

tensology/decisionsai172026年10月10日 更新

One page, hands-on manual tier — drive a live page through the web accessibility (a11y) checks a rule engine can't decide: keyboard operation and focus order, screen-reader names, roles and states from the accessibility tree, reflow and zoom, reduced motion, form errors, and target size. Grades each finding by evidence basis (verified / confirm-with-a-human / human-required) and severity, and closes every criterion in a ledger: verified, flagged, not exercised, or N/A. Locates and assesses; does not fix (use `accessibility-fix`). Use it for keyboard testing, focus-order checks, screen-reader or a11y-tree review, reflow and zoom at 200%, or 'is this operable, not just lint-clean'. The automated tier is `accessibility-scan`; `accessibility-audit` runs both across a sampled site.

日本語の概要は準備中です。原文の説明を表示しています。

tensology/decisionsai172026年10月10日 更新

One page, automated tier — run the web accessibility (a11y) rule engine against a live page and locate every violation it can detect mechanically. Pass a URL, a config target name (e.g. `accesslint:accessibility-scan dev`), or nothing to use the default target from `accesslint.config.json`. Ensures a debuggable Chrome, runs the @accesslint/core engine over CDP, and returns a worklist of live-DOM WCAG 2.2 violations, each grounded to its DOM selector and source `file:line`. Locates; doesn't edit. Use it for 'is this page accessible', 'check a11y on this URL', 'find contrast and alt-text issues', or to verify a UI change. For hands-on keyboard and screen-reader checks use `accessibility-inspect`; for a whole site or product use `accessibility-audit`; to diff against uncommitted changes or a branch use `accessibility-diff`.

日本語の概要は準備中です。原文の説明を表示しています。

tensology/decisionsai172026年10月10日 更新

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