Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add L-LesterYu/OpenClaw-hot-skills-zh --skill nano-banana-pro-prompts-recommend-skill-zhgit clone --depth 1 https://github.com/L-LesterYu/OpenClaw-hot-skills-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-prompts-recommend-skill-zh)<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-prompts-recommend-skill-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-prompts-recommend-skill-zh/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-prompts-recommend-skill-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-prompts-recommend-skill-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00241 | $0.03968 |
| Opus 5 | $0.00120 | $0.01984 |
| Sonnet 5 | $0.00048 | $0.00794 |
| Haiku 4.5 | $0.00024 | $0.00397 |
Grade A, and why
nano-banana-pro-prompts-recommend-skill scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
exec: curl -fsSL "{sourceMedia[0]}" -o /tmp/prompt_img.jpg This is a copy
91% identical to ai-image-prompts-skill — 111 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 399 lines — stays where its author put it; the contents beside it link to each section on GitHub.
📖 提示词由 YouMind 精选 · 10,000+ 社区提示词 · 尝试生成图像 →
�️ 寻找模型无关版本?试试 ai-image-prompts — 同样的库,通用定位。
Nano Banana Pro 提示词推荐
您是来自 Nano Banana Pro 提示词库(10,000+ 提示词)的图像生成提示词推荐专家。这些提示词针对 Nano Banana Pro(Google Gemini)进行了优化,但也适用于任何文本到图像模型,包括 Nano Banana 2、Seedream 5.0、GPT Image 1.5、Midjourney、DALL-E 3、Flux 和 Stable Diffusion。
⚠️ 关键:示例图片是必需的
每个提示词推荐必须包含其示例图片。 这不是可选的 — 图片是这个技能的核心价值。用户在选择前需要看到每个提示词生成的效果。
- 每个提示词都有
sourceMedia[]— 总是发送sourceMedia[0]作为图片 - 如果
sourceMedia为空,完全跳过该提示词 - 永远不要只以文本形式展示提示词 — 总是附加图片
快速开始
用户提供图像生成需求 → 您推荐匹配的提示词 并附带示例图片 → 用户选择提示词 → (如果提供了内容)混音创建自定义提示词。
两种使用模式
- 直接生成:用户描述他们想要的图像 → 推荐提示词 → 完成
- 内容插图:用户提供内容(文章/视频脚本/播客笔记)→ 推荐提示词 → 用户选择 → 收集个性化信息 → 基于他们的内容生成自定义提示词
设置
安装此技能后,提示词库会通过 postinstall 自动从 GitHub 下载。不需要凭据 — 所有数据都是公开可用的。
如果引用文件缺失,请手动运行:
node scripts/setup.js
保持引用文件最新(GitHub 每日同步社区提示词两次):
# 强制拉取最新引用(建议每周执行)
pnpm run sync
# 或等效命令
node scripts/setup.js --force
在步骤 2 之前,检查引用文件是否过期(>24小时未更新):
node scripts/setup.js --check
This fetches the latest references/*.json files from:
https://github.com/YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill/tree/main/references
Available Reference Files
The references/ directory contains categorized prompt data (auto-generated daily by GitHub Actions).
Categories are dynamic — read references/manifest.json to get the current list:
// references/manifest.json (example)
{
"updatedAt": "2026-02-28T10:00:00Z",
"totalPrompts": 10224,
"categories": [
{ "slug": "social-media-post", "title": "Social Media Post", "file": "social-media-post.json", "count": 6382 },
{ "slug": "product-marketing", "title": "Product Marketing", "file": "product-marketing.json", "count": 3709 }
// ... more categories
]
}
When starting a search, load the manifest first to know what categories exist:
cat {SKILL_DIR}/references/manifest.json
Then use the slug and title fields to match user intent to the right file.
What ships with it
25 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .claude-plugin/marketplace.json 516 B
- .github/workflows/generate-references.yml 1.3 KB
- .gitignore 42 B
- package.json 1.6 KB
- pnpm-lock.yaml 11 KB
- public/cover.png 1828 KB
- PUBLISHING.md 3.4 KB
- README.md 9.3 KB
- references/.gitkeep 0 B
- references/.last-updated 13 B
- references/app-web-design.json 267 KB
- references/comic-storyboard.json 489 KB
- references/ecommerce-main-image.json 928 KB
- references/game-asset.json 741 KB
- references/infographic-edu-visual.json 744 KB
- references/manifest.json 1.6 KB
- references/others.json 1107 KB
- references/poster-flyer.json 1048 KB
- references/product-marketing.json 10427 KB
- references/profile-avatar.json 2813 KB
- references/social-media-post.json 17520 KB
- references/youtube-thumbnail.json 320 KB
- scripts/generate-references.ts 11 KB runs code
- scripts/setup.js 4.2 KB runs code
- tsconfig.json 414 B
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 399 lines · 241 tokens per session scan A 61e53f58654e
nano-banana-pro-prompts-recommend-skill is a skill published in the GitHub repository L-LesterYu/OpenClaw-hot-skills-zh (54 stars, last pushed 5mo ago), licensed MIT. It adds 241 tokens to every session and 3,968 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 91% identical to ai-image-prompts-skill, differing in 111 lines, and is treated as a copy.
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