MCPInstall

sf-diagram-nanobananapro

AI-powered image generation for Salesforce visuals via Nano Banana Pro. TRIGGER when: user asks for PNG/SVG output, UI mockups, wireframes, visual ERDs, or says "generate image" / "create mockup". DO NOT TRIGGER when: text-based Mermaid diagrams (use sf-diagram-mermaid), or non-visual documentation tasks.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/jaganpro/sf-skills --skill sf-diagram-nanobananapro
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads sf-diagram-nanobananapro automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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:

  • 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
  • metadata discovery for ERDs → sf-metadata
  • LWC implementation after the mockup → sf-lwc
  • Apex review / implementation → sf-apex

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

Request typeAsk about
ERD / schemaobjects, visual style, purpose, extras
UI mockupcomponent type, object/context, device/layout, style
architecture imagesystems, boundaries, protocols, emphasis
image editwhat 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:

  • 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

PatternDefault approach
visual ERDget metadata if available, then render a draft first
LWC mockupuse component template + user context + one draft iteration
architecture illustrationemphasize systems and flows, reduce field-level detail
image refinementuse /edit for small changes before regenerating
final production assetswitch to script-driven 2K/4K generation

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

NeedDelegate toReason
Mermaid first draft or text diagramsf-diagram-mermaidfaster structural diagramming
object / field discovery for ERDsf-metadataaccurate schema grounding
turn mockup into real componentsf-lwcimplementation after design
review Apex / trigger code in parallelsf-apexcode-quality follow-up

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

ScoreMeaning
70+strong image prompt / workflow choice
55–69usable draft with iteration needed
40–54partial alignment to request
< 40poor fit; re-interview and rebuild prompt

FAQ

What does the sf-diagram-nanobananapro skill do?

AI-powered image generation for Salesforce visuals via Nano Banana Pro. TRIGGER when: user asks for PNG/SVG output, UI mockups, wireframes, visual ERDs, or says "generate image" / "create mockup". DO NOT TRIGGER when: text-based Mermaid diagrams (use sf-diagram-mermaid), or non-visual documentation tasks.

How do I install sf-diagram-nanobananapro?

Run npx skills add https://github.com/jaganpro/sf-skills --skill sf-diagram-nanobananapro in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/sf-diagram-nanobananapro/ (personal) or .claude/skills/sf-diagram-nanobananapro/ (project).

Which AI agents can use sf-diagram-nanobananapro?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is sf-diagram-nanobananapro safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains sf-diagram-nanobananapro?

It is published by jaganpro in jaganpro/sf-skills. It has 1,333 recorded installs.

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