MCP servers · Python · v0.1.0
Curated skills, sub-agents, and config templates that supercharge Claude Code — research, image gen, GitHub automation & more.
#agentic-ai#agents#ai
Generate or edit images via Google Gemini (nanobanana). This is the DEFAULT image skill — use whenever the user asks to generate, create, or edit an image and does NOT name another provider. Triggers: "nanobanana", "generate image", "create image", "edit image", "图片生成", "生成图片", "AI绘图", "图片编辑". Do NOT use for diagrams (架构图/流程图/时序图) — draw those with Mermaid or code instead.
by feiskyer · updated 1mo ago · imported from GitHub
Generate or edit images using Google Gemini API through the nanobanana tool.
~/.nanobanana.env or export GEMINI_API_KEY=<your-api-key>python3 -m pip install -r ${CLAUDE_SKILL_DIR}/requirements.txt if not installed yet.${CLAUDE_SKILL_DIR}/nanobanana.pyAsk the user for:
Run the nanobanana script with appropriate parameters:
python3 ${CLAUDE_SKILL_DIR}/nanobanana.py --prompt "description of image" --output "filename.png"
Show the user the saved image path when complete
Ask the user for:
Run with input images:
python3 ${CLAUDE_SKILL_DIR}/nanobanana.py --prompt "editing instructions" --input image1.png image2.png --output "edited.png"
1024x1024 (1:1) - Square832x1248 (2:3) - Portrait1248x832 (3:2) - Landscape864x1184 (3:4) - Portrait1184x864 (4:3) - Landscape896x1152 (4:5) - Portrait1152x896 (5:4) - Landscape768x1344 (9:16) - Portrait (default)1344x768 (16:9) - Landscape1536x672 (21:9) - Ultra-widegemini-3.1-flash-image-preview (default) - Latest, fast generationgemini-3-pro-image-preview - Higher quality, supports thinking/reasoning1K (default)2K4K--no-search - Disable Google Search grounding (enabled by default)--no-think - Disable thinking/reasoning modepython3 ${CLAUDE_SKILL_DIR}/nanobanana.py --prompt "A serene mountain landscape at sunset with a lake"
python3 ${CLAUDE_SKILL_DIR}/nanobanana.py \
--prompt "Modern minimalist logo for a tech startup" \
--size 1024x1024 \
--output "logo.png"
python3 ${CLAUDE_SKILL_DIR}/nanobanana.py \
--prompt "Futuristic cityscape with flying cars" \
--size 1344x768 \
--resolution 2K \
--output "cityscape.png"
python3 ${CLAUDE_SKILL_DIR}/nanobanana.py \
--prompt "Add a rainbow in the sky" \
--input photo.png \
--output "photo-with-rainbow.png"
python3 ${CLAUDE_SKILL_DIR}/nanobanana.py \
--prompt "Detailed portrait of a cat in watercolor style" \
--model gemini-3-pro-image-preview \
--output "cat-portrait.png"
If the script fails:
GEMINI_API_KEY is exported or set in ~/.nanobanana.envNo comments yet — start the thread.
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MCP servers · Python · v0.1.0
Curated skills, sub-agents, and config templates that supercharge Claude Code — research, image gen, GitHub automation & more.
#agentic-ai#agents#ai
Prompts · Python · v0.1.0
Explore user intent, requirements, and design options through collaborative dialogue before implementation. Use before building new features, components, or systems — whenever the user describes something to build and design decisions are involved. Triggers: "brainstorm", "help me design", "think through the requirements", "头脑风暴", "设计方案", "梳理需求". Not for bug fixes, config changes, or tasks with an obvious implementation path.
#agentic-ai#agents#ai
Prompts · Python · v0.1.0
Leverage OpenAI Codex/GPT models for autonomous code implementation, code review, and plan review. Triggers: "codex", "use gpt", "gpt-5", "let openai", "full-auto", "adversarial review", "second opinion review", "用codex", "让gpt实现", "对抗式审查", "让codex审查计划", "第二意见". Use this skill whenever the user wants to delegate coding tasks to OpenAI models, run code or plan reviews via codex, get a second-opinion review from a different model, or execute tasks in a sandboxed environment.
#agentic-ai#agents#ai
Prompts · Python · v0.1.0
Multi-agent research orchestration: split a research goal into parallel sub-goals, run each via headless `claude -p` subprocesses, aggregate results into a polished report file. Use for systematic web/document research, competitive or industry analysis, batch link/dataset processing, and long-form evidence synthesis. Triggers: "深度调研", "deep research", "wide research", "多 Agent 调研", "系统调研".
#agentic-ai#agents#ai