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google-gemini-media

Use the Gemini API (Nano Banana image generation, Veo video, Gemini TTS speech and audio understanding) to deliver end-to-end multimodal media workflows and…

Skill by ShenWang96

IndexedMIT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Use the Gemini API (Nano Banana image generation, Veo video, Gemini TTS speech and audio understanding) to deliver end-to-end multimodal media workflows and code templates for "generation + understanding".

Use cases: backend

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/google-gemini-media

What's inside

Skill name
google-gemini-media
Description
Use the Gemini API (Nano Banana image generation, Veo video, Gemini TTS speech and audio understanding) to deliver end-to-end multimodal media workflows and code templates for "generation + understanding".
License
MIT
Instructions
450 lines in SKILL.md · view on GitHub

Before installing

  • Instructions call the network

Files (2)

  • origin.json · .clawdhub/
  • SKILL.md

SKILL.md (first lines)

# Gemini Multimodal Media (Image/Video/Speech) Skill

## 1. Goals and scope

This Skill consolidates six Gemini API capabilities into reusable workflows and implementation templates:

- Image generation (Nano Banana: text-to-image, image editing, multi-turn iteration)
- Image understanding (caption/VQA/classification/comparison, multi-image prompts; supports inline and Files API)
- Video generation (Veo 3.1: text-to-video, aspect ratio/resolution control, reference-image guidance, first/last frames, video extension, native audio)
- Video understanding (upload/inline/YouTube URL; summaries, Q&A, timestamped evidence)
- Speech generation (Gemini native TTS: single-speaker and multi-speaker; controllable style/accent/pace/tone)
- Audio understanding (upload/inline; description, transcription, time-range transcription, token counting)

> Convention: This Skill follows the official Google Gen AI SDK (Node.js/REST) as the main line; currently only Node.js/REST examples are provided. If your project already wraps other languages or frameworks, map this Skill's request structure, model selection, and I/O spec to your wrapper layer.

---

## 2. Quick routing (decide which capability to use)

1) **Do you need to produce images?**
- Need to generate images from scratch or edit based on an image -> use **Nano Banana image generation** (see Section 5)

2) **Do you need to understand images?**
- Need recognition, description, Q&A, comparison, or info extraction -> use **Image understanding** (see Section 6)

3) **Do you need to produce video?**
- Need to generate an 8-second video (optionally with native audio) -> use **Veo 3.1 video generation** (see Section 7)

4) **Do you need to understand video?**
- Need summaries/Q&A/segment extraction with timestamps -> use **Video understanding** (see Section 8)

5) **Do you need to read text aloud?**
- Need controllable narration, podcast/audiobook style, etc. -> use **Speech generation (TTS)** (see Section 9)

6) **Do you need to understand audio?**
- Need audio descriptions, transcription, time-range transcription, token counting -> use **Audio understanding** (see Section 10)

---

## 3. Unified engineering constraints and I/O spec (must read)

### 3.0 Prerequisites (dependencies and tools)

- Node.js 18+ (match your project version)
- Install SDK (example):
```bash
npm install @google/genai
```
- REST examples only need `curl`; if you need to parse image Base64, install `jq` (optional).

### 3.1 Authentication and environment variables

- Put your API key in `GEMINI_API_KEY`
- REST requests use `x-goog-api-key: $GEMINI_API_KEY`

### 3.2 Two file input modes: Inline vs Files API

**Inline (embedded bytes/Base64)**
- Pros: shorter call chain, good for small files.
- Key constraint: total request size (text prompt + system instructions + embedded bytes) typically has a ~20MB ceiling.

**Files API (upload then reference)**
- Pros: good for large files, reusing the same file, or multi-turn conversations.
- Typical flow:
  1. `files.upload(...)` (SDK) or `POST /upload/v1beta/files` (REST resumable)
  2. Use `file_data` / `file_uri` in `generateContent`

> Engineering suggestion: implement `ensure_file_uri()` so that when a file exceeds a threshold (for example 10-15MB warning) or is reused, you automatically route through the Files API.

### 3.3 Unified handling of binary media outputs

- **Images**: usually returned as `inline_data` (Base64) in response parts; in the SDK use `part.as_image()` or decode Base64 and save as PNG/JPG.
- **Speech (TTS)**: usually returns **PCM** bytes (Base64); save as `.pcm` or wrap into `.wav` (commonly 24kHz, 16-bit, mono).
- **Video (Veo)**: long-running async task; poll the operation; download the file (or use the returned URI).

---

## 4. Model selection matrix (choose by scenario)

> Important: model names, versions, limits, and quotas can change over time. Verify against official docs before use. Last updated: 2026-01-22.

### 4.1 Image generation (Nano Banana)
- **gemini-2.5-flash-image**: optimized for speed/throughput; good for frequent, low-latency generation/editing.
- **gemini-3-pro-image-preview**: stronger instruction following and high-fidelity text rendering; better for professional assets and complex edits.

### 4.2 General image/video/audio understanding
- Docs use `gemini-3-flash-preview` for image, video, and audio understanding (choose stronger models as needed for quality/cost).

### 4.3 Video generation (Veo)
- Example model: `veo-3.1-generate-preview` (generates 8-second video and can natively generate audio).

### 4.4 Speech generation (TTS)
- Example model: `gemini-2.5-flash-preview-tts` (native TTS, currently in preview).

---

## 5. Image generation (Nano Banana)

### 5.1 Text-to-Image

**SDK (Node.js) minimal template**
```js
import { GoogleGenAI } from "@google/genai";
import * as fs from "node:fs";

const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY });

const response = await ai.models.generateContent({
  model: "gemini-2.5-flash-image",
  contents:
    "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme",
});

const parts = response.candidates?.[0]?.content?.parts ?? [];
for (const part of parts) {
  if (part.text) console.log(part.text);
  if (part.inlineData?.data) {
    fs.writeFileSync("out.png", Buffer.from(part.inlineData.data, "base64"));
  }

From ShenWang96/clawdbot_workspace_backup, MIT.

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Last commit (this folder)
Feb 18, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

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License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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google-gemini-media skill. Agent Mart. https://agentmart.dev/skills/shenwang96-google-gemini-media (last updated 2026-10-24)