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:

skills/sf-diagram-nanobananapro/scripts/check-prerequisites.sh

If prerequisites fail, stop and route the user to setup guidance in:

• references/gemini-cli-setup.md

When This Skill Owns the Task

Use @sf-diagram-nanobananapro when the user wants:

• PNG / SVG-style image output
• rendered ERDs or architecture diagrams
• LWC or Experience Cloud mockups / wireframes
• visual polish beyond Mermaid
• edits to a previously generated image

Delegate elsewhere when the user wants:

• Mermaid or text-only diagrams → [sf-diagram-mermaid](../sf-diagram-mermaid/rule file)
• metadata discovery for ERDs → [sf-metadata](../sf-metadata/rule file)
• LWC implementation after the mockup → [sf-lwc](../sf-lwc/rule file)
• Apex review / implementation → [sf-apex](../sf-apex/rule file)

Required Context to Gather First

Ask for or infer:

• image type: ERD, UI mockup, architecture illustration, or image edit
• subject scope and key entities / systems
• target quality: draft vs presentation vs production asset
• preferred style and aspect ratio
• 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

Question bank: references/interview-questions.md

Quick mode defaults

If the user says “quick”, “simple”, or “just generate”, default to:

• professional style
• 1K draft output
• legend included when helpful
• one image first, then iterate

Recommended Workflow

1. Gather inputs

Decide which of these are needed:

• object list / metadata
• purpose: draft vs presentation vs documentation
• desired aesthetic
• aspect ratio / resolution
• whether this is a fresh render or edit of an existing image

2. Build a concrete prompt

Good prompts specify:

• subject and scope
• composition / layout
• color treatment
• labels / legends / relationship lines
• 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:

• dark border + light fill cards
• cloud-specific accent colors
• clean labels and relationship lines
• presentation-ready whitespace and hierarchy

Style guide: references/architect-aesthetic-guide.md

Common Patterns

Examples: references/examples-index.md

Output / Review Guidance

After generating, do one of these:

• open the file in Preview for visual inspection
• attach/read the image in the coding session for multimodal review
• 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

Reference Map

Start here

• references/gemini-cli-setup.md
• references/interview-questions.md
• references/iteration-workflow.md

Visual style / examples

• references/architect-aesthetic-guide.md
• references/examples-index.md
• assets/erd/
• assets/lwc/
• assets/architecture/
• assets/review/

Score Guide