AgentSkillsCN

nano-banana-pro

借助 nano-pdf CLI，通过自然语言指令编辑 PDF 文件。

SKILL.md
--- frontmatter
name: nano-banana-pro
description: Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Use for image create/modify requests incl. edits. Supports text-to-image + image-to-image; 1K/2K/4K; use --input-image.
requires:
  env:
    - name: GEMINI_API_KEY
      prompt: "Provide your Gemini API key for Nano Banana Pro (it will be stored in skills_secrets.yml and used to call Google's Gemini image API)."
      example: "AIzaSy..."
  pip:
    - google-genai
    - pillow

Nano Banana Pro Image Generation & Editing

Generate new images or edit existing ones using Google's Nano Banana Pro API (Gemini 3 Pro Image).

Usage

Dependencies

This skill requires these Python packages:

  • •google-genai (Gemini client)
  • •pillow (image I/O)

Install them with uv (recommended):

bash
uv pip install google-genai pillow

Note: scripts/generate_image.py also includes inline script metadata (PEP 723) so uv run ... can auto-resolve these dependencies, but pre-installing is faster for repeated runs.

Run the script using the skill's installed path (provided in system prompt as → file_read(path="skills/SKILL.md")).

Generate new image:

bash
uv run skills/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--resolution 1K|2K|4K] [--api-key KEY]

Edit existing image:

bash
uv run skills/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 1K|2K|4K] [--api-key KEY]

Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.

Default Workflow (draft → iterate → final)

Goal: fast iteration without burning time on 4K until the prompt is correct.

  • •Draft (1K): quick feedback loop
    • •uv run skills/scripts/generate_image.py --prompt "<draft prompt>" --filename "yyyy-mm-dd-hh-mm-ss-draft.png" --resolution 1K
  • •Iterate: adjust prompt in small diffs; keep filename new per run
    • •If editing: keep the same --input-image for every iteration until you’re happy.
  • •Final (4K): only when prompt is locked
    • •uv run skills/scripts/generate_image.py --prompt "<final prompt>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K

Resolution Options

The Gemini 3 Pro Image API supports three resolutions (uppercase K required):

  • •1K (default) - ~1024px resolution - PREFERRED for most requests
  • •2K - ~2048px resolution
  • •4K - ~4096px resolution

Default behavior: Always use 1K unless the user explicitly requests higher resolution.

Map user requests to API parameters:

  • •No mention of resolution → 1K (default)
  • •"low resolution", "1080", "1080p", "1K", "quick", "fast", "draft" → 1K
  • •"2K", "2048", "normal", "medium resolution" → 2K
  • •"high resolution", "high-res", "hi-res", "4K", "ultra", "best quality", "final" → 4K

Important: Prefer lower resolution (1K) to save time and resources. Only use higher resolutions when the user specifically asks for quality/resolution.

API Key

The script checks for API key in this order:

  1. •--api-key argument (use if user provided key in chat)
  2. •GEMINI_API_KEY environment variable

If neither is available, the script exits with an error message.

Preflight + Common Failures (fast fixes)

  • •

    Preflight:

    • •command -v uv (must exist)
    • •test -n \"$GEMINI_API_KEY\" (or pass --api-key)
    • •If editing: test -f \"path/to/input.png\"
  • •

    Common failures:

    • •Error: No API key provided. → set GEMINI_API_KEY or pass --api-key
    • •Error loading input image: → wrong path / unreadable file; verify --input-image points to a real image
    • •“quota/permission/403” style API errors → wrong key, no access, or quota exceeded; try a different key/account

Filename Generation

Generate filenames with the pattern: yyyy-mm-dd-hh-mm-ss-name.png

Format: {timestamp}-{descriptive-name}.png

  • •Timestamp: Current date/time in format yyyy-mm-dd-hh-mm-ss (24-hour format)
  • •IMPORTANT: Generate the actual timestamp value (e.g., 2026-01-29-13-30-45), do NOT use shell syntax like $(date ...)
  • •Name: Descriptive lowercase text with hyphens
  • •Keep the descriptive part concise (1-5 words typically)
  • •Use context from user's prompt or conversation
  • •If unclear, use random identifier (e.g., x9k2, a7b3)

Examples:

  • •Prompt "A serene Japanese garden" → 2025-11-23-14-23-05-japanese-garden.png
  • •Prompt "sunset over mountains" → 2025-11-23-15-30-12-sunset-mountains.png
  • •Prompt "create an image of a robot" → 2025-11-23-16-45-33-robot.png
  • •Unclear context → 2025-11-23-17-12-48-x9k2.png

Image Editing

When the user wants to modify an existing image:

  1. •Check if they provide an image path or reference an image in the current directory
  2. •Use --input-image parameter with the path to the image
  3. •The prompt should contain editing instructions (e.g., "make the sky more dramatic", "remove the person", "change to cartoon style")
  4. •Common editing tasks: add/remove elements, change style, adjust colors, blur background, etc.

Prompt Handling

For generation: Pass user's image description as-is to --prompt. Only rework if clearly insufficient.

For editing: Pass editing instructions in --prompt (e.g., "add a rainbow in the sky", "make it look like a watercolor painting")

Preserve user's creative intent in both cases.

Prompt Templates (high hit-rate)

Use templates when the user is vague or when edits must be precise.

  • •

    Generation template:

    • •“Create an image of: <subject>. Style: <style>. Composition: <camera/shot>. Lighting: <lighting>. Background: <background>. Color palette: <palette>. Avoid: <list>.”
  • •

    Editing template (preserve everything else):

    • •“Change ONLY: <single change>. Keep identical: subject, composition/crop, pose, lighting, color palette, background, text, and overall style. Do not add new objects. If text exists, keep it unchanged.”

Output

  • •Saves PNG to current directory (or specified path if filename includes directory)
  • •Script outputs the full path to the generated image
  • •After generating: Use send_file(file_path="<full_path>") to send the image to the user
  • •Do not read the image back - just send it with send_file

Examples

Generate new image:

bash
uv run skills/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-11-23-14-23-05-japanese-garden.png" --resolution 4K

Edit existing image:

bash
uv run skills/scripts/generate_image.py --prompt "make the sky more dramatic with storm clouds" --filename "2025-11-23-14-25-30-dramatic-sky.png" --input-image "original-photo.jpg" --resolution 2K