Agent skill

Fal AI Media

by affaan-m in affaan-m/ECC

fal.ai MCPによる統合メディア生成(画像、動画、音声)。テキストから画像(Nano Banana)、テキスト/画像から動画(Seedance、Kling、Veo 3)、テキストから音声(CSM-1B)、動画から音声(ThinkSound)をカバーします。ユーザーがAIで画像、動画、音声を生成したい場合に使用します。

MITAuto-check passedMedia & Creative

Install Fal AI Media

skills CLI
$ npx skills add affaan-m/ECC --skill fal-ai-media -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install affaan-m/ECC fal-ai-media --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/ja-JP/skills/fal-ai-media .claude/skills/fal-ai-media && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
fal-ai-media
GitHub stars
276k
Token cost
~1.4k tokens
SKILL.md length
153 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

fal.ai MCPによる統合メディア生成(画像、動画、音声)。テキストから画像(Nano Banana)、テキスト/画像から動画(Seedance、Kling、Veo 3)、テキストから音声(CSM-1B)、動画から音声(ThinkSound)をカバーします。ユーザーがAIで画像、動画、音声を生成したい場合に使用します。

  • Tasks that involve AI video generation
  • SKILL.md covers アクティベートするタイミング, MCP要件, MCPツール and 画像生成, plus 6 more sections
  • Reaches api.elevenlabs.io; needs FAL_KEY and ELEVENLABS_API_KEY
  • Tasks that involve Image generation

What it does

Fal AI Media is an agent skill from affaan-m/ECC. fal.ai MCPによる統合メディア生成(画像、動画、音声)。テキストから画像(Nano Banana)、テキスト/画像から動画(Seedance、Kling、Veo 3)、テキストから音声(CSM-1B)、動画から音声(ThinkSound)をカバーします。ユーザーがAIで画像、動画、音声を生成したい場合に使用します。

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative, covering AI video generation and Image generation. It works with fal, Model Context Protocol, Google Gemini and Google Veo. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • Tasks that involve AI video generation
  • Tasks that involve Image generation

Example prompts

  • “/fal-ai-media”

Requirements

  • Python 3
  • A credential in FAL_KEY
  • A credential in ELEVENLABS_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 4eb71d9. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.elevenlabs.io

    Also links to:

    • fal.ai

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • FAL_KEY
    • ELEVENLABS_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Fal AI Media loads about 1.4k tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 153 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from affaan-m/ECC at commit 4eb71d9, republished under its MIT licence (© affaan-m). 153 words, ~1,418 tokens.

Download SKILL.mdSave it as .claude/skills/fal-ai-media/SKILL.md (or your agent's skills folder).
name
fal-ai-media
description
fal.ai MCPによる統合メディア生成(画像、動画、音声)。テキストから画像(Nano Banana)、テキスト/画像から動画(Seedance、Kling、Veo 3)、テキストから音声(CSM-1B)、動画から音声(ThinkSound)をカバーします。ユーザーがAIで画像、動画、音声を生成したい場合に使用します。
origin
ECC

fal.aiメディア生成

変化が早いスキル。 fal.aiのモデルID、価格、入力、MCPツール名は急速に変わります。特定のモデル、パラメーター、出力形式、またはコストを約束する前に、現在のモデルメタデータを検索または取得してください。

MCPを通じてfal.aiモデルを使用して画像、動画、音声を生成します。

アクティベートするタイミング

  • ユーザーがテキストプロンプトから画像を生成したい場合
  • テキストまたは画像から動画を作成する場合
  • 音声、音楽、または効果音を生成する場合
  • あらゆるメディア生成タスク
  • ユーザーが「generate image」「create video」「text to speech」「make a thumbnail」などと言う場合

MCP要件

fal.ai MCPサーバーを設定する必要があります。~/.claude.jsonに追加してください:

json
"fal-ai": {
  "command": "npx",
  "args": ["-y", "fal-ai-mcp-server"],
  "env": { "FAL_KEY": "YOUR_FAL_KEY_HERE" }
}

APIキーはfal.aiで取得してください。

MCPツール

fal.ai MCPは以下のツールを提供します:

  • search — キーワードで利用可能なモデルを検索
  • find — モデルの詳細とパラメーターを取得
  • generate — パラメーターでモデルを実行
  • result — 非同期生成のステータスを確認
  • status — ジョブステータスを確認
  • cancel — 実行中のジョブをキャンセル
  • estimate_cost — 生成コストを見積もる
  • models — 人気モデルの一覧表示
  • upload — 入力として使用するファイルをアップロード

画像生成

Nano Banana 2(高速)

ベストユースケース: クイックイテレーション、ドラフト、テキストから画像、画像編集。

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(高忠実度)

ベストユースケース: 本番画像、リアリズム、タイポグラフィ、詳細なプロンプト。

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
  }
)
一般的な画像パラメーター
パラメーター型オプション備考
promptstring必須生成したいものを説明する
image_sizestringsquare、portrait_4_3、landscape_16_9、portrait_16_9、landscape_4_3アスペクト比
num_imagesnumber1-4生成する数
seednumber任意の整数再現性
guidance_scalenumber1-20プロンプトへの追従度(高いほど文字通り)
画像編集

インペインティング、アウトペインティング、またはスタイル転送にNano Banana 2を入力画像と共に使用:

# まずソース画像をアップロード
upload(file_path: "/path/to/image.png")

# 次に画像入力で生成
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"
  }
)

動画生成

Seedance 1.0 Pro(ByteDance)

ベストユースケース: テキストから動画、高モーション品質の画像から動画。

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

ベストユースケース: ネイティブ音声生成付きのテキスト/画像から動画。

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)

ベストユースケース: 生成された音声付き、高視覚品質の動画。

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"
  }
)
画像から動画

既存の画像から開始:

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"
  }
)
動画パラメーター
パラメーター型オプション備考
promptstring必須動画を説明する
durationstring"5s"、"10s"動画の長さ
aspect_ratiostring"16:9"、"9:16"、"1:1"フレーム比率
seednumber任意の整数再現性
image_urlstringURL画像から動画用のソース画像

音声生成

CSM-1B(会話的スピーチ)

自然な会話品質のテキストから音声。

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(動画から音声)

動画コンテンツからマッチする音声を生成。

generate(
  app_id: "fal-ai/thinksound",
  input_data: {
    "video_url": "<video_url>",
    "prompt": "ambient forest sounds with birds chirping"
  }
)
ElevenLabs(API経由、MCPなし)

プロフェッショナルな音声合成には、ElevenLabsを直接使用:

python
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生成音声

VideoDBが設定されている場合、その生成音声を使用:

python
# 音声生成
audio = coll.generate_voice(text="Your narration here", voice="alloy")

# 音楽生成
music = coll.generate_music(prompt="upbeat electronic background music", duration=30)

# 効果音
sfx = coll.generate_sound_effect(prompt="thunder crack followed by rain")

コスト見積もり

生成前に見積もりコストを確認:

estimate_cost(
  estimate_type: "unit_price",
  endpoints: {
    "fal-ai/nano-banana-pro": {
      "unit_quantity": 1
    }
  }
)

モデル探索

特定のタスクに対するモデルを検索:

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

ヒント

  • プロンプトを繰り返す際の再現性のためにseedを使用する
  • プロンプトのイテレーションには低コストのモデル(Nano Banana 2)から始め、最終版ではProに切り替える
  • 動画の場合、プロンプトはモーションとシーンに焦点を当てて説明的だが簡潔に
  • 画像から動画は純粋なテキストから動画よりも制御された結果を生成する
  • 高コストの動画生成を実行する前にestimate_costを確認する

関連スキル

  • videodb — 動画処理、編集、ストリーミング
  • video-editing — AI駆動の動画編集ワークフロー
  • content-engine — ソーシャルプラットフォーム向けコンテンツ作成

© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in docs/ja-JP/skills/fal-ai-media of affaan-m/ECC.

Open the folder on GitHubat commit 4eb71d9

Compare with similar skills

Fal AI Media next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Fal AI Media compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Fal AI Media this skillaffaan-m/ECC276k—~1.4kAutomated safety check: PassMIT
Forge Media Route Layer0x0funky/agent-sprite-forge4.4k—~2.2kAutomated safety check: PassMIT
Higgsfield ModelsOSideMedia/higgsfield-ai-prompt-skill713—~7kAutomated safety check: PassMIT
Seedance Storyboard Generatorliangdabiao/Seedance2-Storyboard-Generator2.6k—~2.2kAutomated safety check: PassNone
Imagesmixs/visual-skills494—~2.1kAutomated safety check: PassCC-BY-4.0
HiggsfieldOSideMedia/higgsfield-ai-prompt-skill713—~9.1kAutomated safety check: PassMIT

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Questions about Fal AI Media

What does Fal AI Media do?

fal.ai MCPによる統合メディア生成(画像、動画、音声)。テキストから画像(Nano Banana)、テキスト/画像から動画(Seedance、Kling、Veo 3)、テキストから音声(CSM-1B)、動画から音声(ThinkSound)をカバーします。ユーザーがAIで画像、動画、音声を生成したい場合に使用します。. Fal AI Media is an agent skill from affaan-m/ECC.

When should I use Fal AI Media?

Fal AI Media fits situations like: tasks that involve AI video generation; tasks that involve Image generation.

How do I install Fal AI Media in Claude Code?

Run `npx skills add affaan-m/ECC --skill fal-ai-media -a claude-code`. Or copy the skill folder (docs/ja-JP/skills/fal-ai-media in affaan-m/ECC) into .claude/skills/fal-ai-media in your project. Claude Code loads it when a task matches its description.

How do I install Fal AI Media in Codex?

Run `npx skills add affaan-m/ECC --skill fal-ai-media -a codex`. Or copy the skill folder (docs/ja-JP/skills/fal-ai-media in affaan-m/ECC) into .agents/skills/fal-ai-media in your project. Codex loads it when a task matches its description.

Can I use Fal AI Media in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill fal-ai-media -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fal-ai-media, .gemini/skills/fal-ai-media, .github/skills/fal-ai-media and .opencode/skills/fal-ai-media in your project.

What does Fal AI Media need to run?

Going by SKILL.md and its folder, Fal AI Media needs credentials named FAL_KEY and ELEVENLABS_API_KEY. Our summary lists: Python 3; A credential in FAL_KEY; A credential in ELEVENLABS_API_KEY.

Does Fal AI Media access the network?

SKILL.md names 2 domains. In commands or code: api.elevenlabs.io; the agent is likely to contact it when it follows the instructions. As links in the text: fal.ai. This is read from the text; nothing was executed.

Is Fal AI Media safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Fal AI Media use?

Fal AI Media is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fal AI Media use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Fal AI Media?

Skills that share tags, products or a category with Fal AI Media: Forge Media Route Layer (0x0funky/agent-sprite-forge, 4.4k stars), Higgsfield Models (OSideMedia/higgsfield-ai-prompt-skill, 713 stars), Seedance Storyboard Generator (liangdabiao/Seedance2-Storyboard-Generator, 2.6k stars) and Image (smixs/visual-skills, 494 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fal AI Media?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,111 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 10, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.