sf-diagram-nanobananapro
使用Nano Banana Pro生成渲染级可视化内容,包括ERD、UI模型、架构图和演示就绪图像
npx skills add jaganpro/sf-skills --skill sf-diagram-nanobananaproBefore / After 效果对比
1 组手动绘制架构图、调整布局、导出多版本、适配不同场景,一张图需要2-3小时
AI自动生成渲染级可视化图像,20分钟获得演示就绪的专业图表
description SKILL.md
sf-diagram-nanobananapro
sf-diagram-nanobananapro: Salesforce Visual AI Skill
Use this skill when the user needs rendered visuals, not text diagrams: ERDs, UI mockups, architecture illustrations, slide-ready images, or image edits using Nano Banana Pro.
Hard Gate: Prerequisites First
Always run the prerequisites check before using the skill:
~/.claude/skills/sf-diagram-nanobananapro/scripts/check-prerequisites.sh
If prerequisites fail, stop and route the user to setup guidance in:
When This Skill Owns the Task
Use sf-diagram-nanobananapro when the user wants:
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PNG / SVG-style image output
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rendered ERDs or architecture diagrams
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LWC or Experience Cloud mockups / wireframes
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visual polish beyond Mermaid
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edits to a previously generated image
Delegate elsewhere when the user wants:
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Mermaid or text-only diagrams → sf-diagram-mermaid
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metadata discovery for ERDs → sf-metadata
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LWC implementation after the mockup → sf-lwc
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Apex review / implementation → sf-apex
Required Context to Gather First
Ask for or infer:
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image type: ERD, UI mockup, architecture illustration, or image edit
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subject scope and key entities / systems
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target quality: draft vs presentation vs production asset
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preferred style and aspect ratio
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whether the user wants quick mode or an interview-driven prompt build
Interview-First Workflow
Unless the user explicitly asks for quick/simple/just generate, ask clarifying questions first.
Minimum question set
Request type Ask about
ERD / schema objects, visual style, purpose, extras
UI mockup component type, object/context, device/layout, style
architecture image systems, boundaries, protocols, emphasis
image edit what to keep, what to change, output quality
Question bank: references/interview-questions.md
Quick mode defaults
If the user says “quick”, “simple”, or “just generate”, default to:
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professional style
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1K draft output
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legend included when helpful
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one image first, then iterate
Recommended Workflow
1. Gather inputs
Decide which of these are needed:
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object list / metadata
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purpose: draft vs presentation vs documentation
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desired aesthetic
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aspect ratio / resolution
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whether this is a fresh render or edit of an existing image
2. Build a concrete prompt
Good prompts specify:
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subject and scope
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composition / layout
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color treatment
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labels / legends / relationship lines
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output quality goal
3. Generate a fast draft first
gemini --yolo "/generate 'Professional Salesforce ERD with Account, Contact, Opportunity; clean legend; white background; Salesforce-style colors'"
4. Iterate before final
Use natural-language edits:
gemini --yolo "/edit 'Move Account to center, thicken relationship lines, add legend in bottom right'"
5. Use the Python script for controlled final output
Use the script when you need higher resolution or explicit edit inputs:
uv run scripts/generate_image.py \
-p "Final production-quality Salesforce ERD with legend and field highlights" \
-f "crm-erd-final.png" \
-r 4K
Full iteration guide: references/iteration-workflow.md
Default Style Guidance
For ERDs, default to the architect.salesforce.com aesthetic unless the user asks otherwise:
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dark border + light fill cards
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cloud-specific accent colors
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clean labels and relationship lines
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presentation-ready whitespace and hierarchy
Style guide: references/architect-aesthetic-guide.md
Common Patterns
Pattern Default approach
visual ERD get metadata if available, then render a draft first
LWC mockup use component template + user context + one draft iteration
architecture illustration emphasize systems and flows, reduce field-level detail
image refinement
use /edit for small changes before regenerating
final production asset switch to script-driven 2K/4K generation
Examples: references/examples-index.md
Output / Review Guidance
After generating, do one of these:
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open the file in Preview for visual inspection
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attach/read the image in the coding session for multimodal review
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ask the user whether to iterate on layout, labeling, or color before finalizing
Keep the first pass cheap; only spend on high-res output after the composition is right.
Cross-Skill Integration
Need Delegate to Reason
Mermaid first draft or text diagram sf-diagram-mermaid faster structural diagramming
object / field discovery for ERD sf-metadata accurate schema grounding
turn mockup into real component sf-lwc implementation after design
review Apex / trigger code in parallel sf-apex code-quality follow-up
Reference Map
Start here
Visual style / examples
Score Guide
Score Meaning
70+ strong image prompt / workflow choice
55–69 usable draft with iteration needed
40–54 partial alignment to request
< 40 poor fit; re-interview and rebuild prompt
Weekly Installs216Repositoryjaganpro/sf-skillsGitHub Stars205First SeenJan 22, 2026Security AuditsGen Agent Trust HubFailSocketPassSnykFailInstalled oncodex209opencode209gemini-cli207cursor207github-copilot204amp202
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