apekshik

fal

設計創意v1.0.1
作者:apekshik更新於 2026-05-11共 2 個版本 · 最新版本釋出於 2026-02-06@clawhub_apekshik/fal
圖片生成影片處理音訊處理#Image Generation

據 AlphaMoat 統計,截至 2026-09,fal 累計下載 3,145 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 3,624 位,在「設計創意」分類(512 個)中排名第 338 位。

累計安裝
209
累計下載
3145
星標
1
全站排名
#3,624
全站前 72% · 「設計創意」前 67%
平台累計安裝累計下載星標評論
ClawHub ↗9830601-
SkillHub ↗20931451—

各平台的計數口徑不同,統計時間不一致。

這個技能是做什麼的

可在 fal.ai 上搜尋、檢視並執行生成式 AI 模型,涵蓋圖像、影片、音訊等任務。

資料釋出於 2026-10-27

可以用來做什麼

  • 搜尋並執行 fal.ai 上的生成模型
  • 檢視模型輸入 schema 與必填項
  • 上傳輸入檔案並取回生成的媒體檔案

什麼時候用

  • 需要用 AI 模型生成圖像、影片、音訊或 3D 內容時

示例提示詞

以下是根據技能文件生成的示例,不代表實際執行結果。

用 fal-ai/flux-2 生成一張 16:9 風景日落圖
搜一下 fal.ai 上可用的影片生成模型

月度資料趨勢

累計下載3145
1989261032312026-03 · 累計下載 20752026-05 · 累計下載 24892026-06 · 累計下載 25992026-07 · 累計下載 28452026-08 · 累計下載 29662026-09 · 累計下載 314526-0326-09
星標1
0122026-03 · 星標 12026-05 · 星標 12026-06 · 星標 12026-07 · 星標 12026-08 · 星標 12026-09 · 星標 126-0326-09

2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。

月份累計下載環比星標
2026-093145—1
2026-082966+4.3%1
2026-072845+9.5%1
2026-062599+4.4%1
2026-052489—1
2026-032075—1

SKILL.md 原文

以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。

4.6 KB · ClawHub v1.0.1
---
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
展開全部(共 179 行)
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:
```bash
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`:

```bash
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:
```bash
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`:

```bash
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**
```bash
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**
```bash
# 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**
```bash
# 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`:

```bash
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`:

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

---

### If $0 = "upload"

Upload file `$1` to fal CDN:

```bash
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`

「設計創意」分類下的熱門技能

資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。