agentmods.dev

nano-banana-pro-zh

nano-banana-pro-zh is a skill for Codex from L-LesterYu/OpenClaw-hot-skills-zh. It costs 69 tokens per session (1,772 once invoked), scanned A, original, MIT.

An image-generation and editing tool built around Google's Nano Banana Pro image model. It creates new images from text or edits existing images, with selectable output resolutions.

In plain words
What is it for?
Use it to generate images from descriptions or modify an existing image using an input file.
Why use it?
Creating or changing images manually can require separate design software and repeated work. Natural-language instructions let you describe the result or the edit directly.

Skill for Codex

Written for Codex: reads ~/.codex or $CODEX_HOME. Also seen: mentions Codex.

not rated 54repo +1 5mo ago A scan 69 tokens original MIT

Good fit Use it to generate images from descriptions or modify an existing image using an input file.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-zh
View source ↗ L-LesterYu/OpenClaw-hot-skills-zh
Install

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.

Any agent
npx skills add L-LesterYu/OpenClaw-hot-skills-zh --skill nano-banana-pro-zh
Clone the repo
git clone --depth 1 https://github.com/L-LesterYu/OpenClaw-hot-skills-zh

Made for: Codex.

Wrote 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.

agentmods badge for nano-banana-pro-zh

README.md
[![agentmods](https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-zh/github.svg)](https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-zh)
Your own site
<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-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.

agentmods 80×15 button for nano-banana-pro-zh

Your own site · 80×15
<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/nano-banana-pro-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,772 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00069 $0.01772
Opus 5 $0.00034 $0.00886
Sonnet 5 $0.00014 $0.00354
Haiku 4.5 $0.00007 $0.00177

Measured 9d ago against content hash d4c2d6781aff, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

nano-banana-pro-zh scanned grade A with 0 findings 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/generate_image.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/nano-banana-pro-zh/SKILL.md · 131 lines

How it starts

The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Nano Banana Pro 图像生成与编辑

使用 Google 的 Nano Banana Pro API (Gemini 3 Pro Image) 生成新图像或编辑现有图像。

使用方法

使用绝对路径运行脚本（请勿先 cd 到技能目录）：

生成新图像：

uv run ~/.codex/skills/nano-banana-pro-zh/scripts/generate_image.py --prompt "你的图像描述" --filename "输出文件名.png" [--resolution 1K|2K|4K] [--api-key KEY]

编辑现有图像：

uv run ~/.codex/skills/nano-banana-pro-zh/scripts/generate_image.py --prompt "编辑指令" --filename "输出文件名.png" --input-image "输入图像路径.png" [--resolution 1K|2K|4K] [--api-key KEY]

重要提示： 始终从用户当前工作目录运行，以便图像保存在用户工作位置，而不是技能目录中。

默认工作流（草稿 → 迭代 → 最终）

目标：快速迭代，在提示词正确之前不要浪费时间生成 4K 图像。

  • 草稿 (1K)：快速反馈循环
    • uv run ~/.codex/skills/nano-banana-pro-zh/scripts/generate_image.py --prompt "<草稿提示词>" --filename "yyyy-mm-dd-hh-mm-ss-draft.png" --resolution 1K
  • 迭代：以小幅差异调整提示词；每次运行保持文件名更新
    • 如果是编辑：每次迭代使用相同的 --input-image 直到满意为止
  • 最终 (4K)：仅在提示词确定后使用
    • uv run ~/.codex/skills/nano-banana-pro-zh/scripts/generate_image.py --prompt "<最终提示词>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K

分辨率选项

Gemini 3 Pro Image API 支持三种分辨率（K 必须大写）：

  • 1K（默认）- 约 1024px 分辨率
  • 2K - 约 2048px 分辨率
  • 4K - 约 4096px 分辨率

将用户请求映射到 API 参数：

  • 未提及分辨率 → 1K
  • "低分辨率"、"1080"、"1080p"、"1K" → 1K
  • "2K"、"2048"、"普通"、"中等分辨率" → 2K
  • "高分辨率"、"高清"、"hi-res"、"4K"、"超清" → 4K

API 密钥

脚本按以下顺序检查 API 密钥：

  1. --api-key 参数（如果用户在聊天中提供了密钥）
  2. GEMINI_API_KEY 环境变量

如果两者都不可用，脚本将退出并显示错误消息。

预检与常见故障（快速修复）

  • 预检：

    • command -v uv（必须存在）
    • test -n \"$GEMINI_API_KEY\"（或传递 --api-key）
    • 如果是编辑：test -f "path/to/input.png"

  • 常见故障：

    • 错误：未提供 API 密钥。 → 设置 GEMINI_API_KEY 或传递 --api-key
    • 加载输入图像时出错： → 路径错误或文件不可读；验证 --input-image 指向真实图像
    • "配额/权限/403" 类 API 错误 → 密钥错误、无访问权限或配额超限；尝试使用不同的密钥/账户

文件名生成

使用以下模式生成文件名：yyyy-mm-dd-hh-mm-ss-name.png

格式： {时间戳}-{描述性名称}.png

  • 时间戳：当前日期/时间，格式为 yyyy-mm-dd-hh-mm-ss（24小时制）
  • 名称：带连字符的描述性小写文本
  • 保持描述部分简洁（通常 1-5 个词）
  • 使用用户提示或对话中的上下文
  • 如果不清楚，使用随机标识符（例如 x9k2、a7b3）

示例：

  • 提示 "宁静的日式花园" → 2025-11-23-14-23-05-japanese-garden.png
  • 提示 "山上的日落" → 2025-11-23-15-30-12-sunset-mountains.png
  • 提示 "创建一个机器人图像" → 2025-11-23-16-45-33-robot.png
  • 上下文不明确 → 2025-11-23-17-12-48-x9k2.png

Read the full file on GitHub · 131 lines

Files

What ships with it

3 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.

Changes

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.

  1. 9d ago First seen · 131 lines · 69 tokens per session scan A d4c2d6781aff

Subscribe to this mod's changes

nano-banana-pro-zh is a skill published in the GitHub repository L-LesterYu/OpenClaw-hot-skills-zh (54 stars, last pushed 5mo ago), licensed MIT. It adds 69 tokens to every session and 1,772 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Creative and media
Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens