sf-diagram-mermaid

jaganpro/sf-skills · updated Apr 8, 2026

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$npx skills add https://github.com/jaganpro/sf-skills --skill sf-diagram-mermaid
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summary

Use this skill when the user needs text-based diagrams: Mermaid diagrams for architecture, OAuth, integration flows, ERDs, or Agentforce structure, plus ASCII fallback when plain-text compatibility matters.

skill.md

sf-diagram-mermaid: Salesforce Diagram Generation

Use this skill when the user needs text-based diagrams: Mermaid diagrams for architecture, OAuth, integration flows, ERDs, or Agentforce structure, plus ASCII fallback when plain-text compatibility matters.

When This Skill Owns the Task

Use sf-diagram-mermaid when the user wants:

  • Mermaid output
  • ASCII fallback diagrams
  • architecture, sequence, flowchart, or ERD views in markdown-friendly form
  • diagrams that can live directly in docs, READMEs, or issues

Delegate elsewhere when the user wants:

  • rendered PNG/SVG images or polished mockups → sf-diagram-nanobananapro
  • non-Salesforce systems only → use a more general diagramming skill
  • object discovery before an ERD → sf-metadata

Supported Diagram Families

Type Preferred Mermaid form Typical use
OAuth / auth flows sequenceDiagram Authorization Code, JWT, PKCE, Device Flow
ERD / data model flowchart LR object relationships and sharing context
integration sequence sequenceDiagram request/response or event choreography
system landscape flowchart high-level architecture
role / access hierarchy flowchart users, profiles, permissions
Agentforce behavior map flowchart agent → topic → action relationships

Required Context to Gather First

Ask for or infer:

  • diagram type
  • scope and entities / systems involved
  • output preference: Mermaid only, ASCII only, or both
  • whether styling should be minimal, documentation-first, or presentation-friendly
  • for ERDs: whether org metadata is available for grounding

Recommended Workflow

1. Pick the right diagram structure

  • use sequenceDiagram for time-ordered interactions
  • use flowchart LR for ERDs and capability maps
  • keep a single primary story per diagram when possible

2. Gather data

For ERDs and grounded diagrams:

  • use sf-metadata when real schema discovery is needed
  • optionally use the local metadata helper script for counts / relationship context when appropriate

3. Generate Mermaid first

Apply:

  • accurate labels
  • simple readable node text
  • consistent relationship notation
  • restrained styling that renders cleanly in markdown viewers

4. Add ASCII fallback when useful

Provide an ASCII version when the user wants terminal compatibility or plaintext documentation.

5. Explain the diagram briefly

Call out the key relationships, flow direction, and any assumptions.


High-Signal Rules

For sequence diagrams

  • use autonumber when step order matters
  • distinguish requests vs responses clearly
  • use notes sparingly for protocol detail

For ERDs

  • prefer flowchart LR
  • keep object cards simple
  • use clear relationship arrows
  • avoid field overload unless the user explicitly asks for field-level detail
  • color-code object types only when it improves readability

For ASCII output

  • keep width reasonable
  • align arrows and boxes consistently
  • optimize for readability over decoration

Output Format

## <Diagram Title>

### Mermaid Diagram
```mermaid
<diagram>
```

### ASCII Fallback
```text
<ascii>
```

### Notes
- <key point>
- <assumption or limitation>

Cross-Skill Integration

Need Delegate to Reason
real object / field definitions sf-metadata grounded ERD generation
rendered diagram / image output sf-diagram-nanobananapro visual polish beyond Mermaid
connected-app auth setup context sf-connected-apps accurate OAuth flows
Agentforce logic visualization sf-ai-agentscript source-of-truth behavior details
Flow behavior diagrams sf-flow actual Flow logic grounding

Reference Map

Start here

Styling / ERD specifics

Preview


Score Guide

Score Meaning
72–80 production-ready diagram
60–71 clear and useful with minor polish left
48–59 functional but could be clearer
35–47 needs structural improvement
< 35 inaccurate or incomplete
how to use sf-diagram-mermaid

How to use sf-diagram-mermaid on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add sf-diagram-mermaid
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jaganpro/sf-skills --skill sf-diagram-mermaid

The skills CLI fetches sf-diagram-mermaid from GitHub repository jaganpro/sf-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/sf-diagram-mermaid

Reload or restart Cursor to activate sf-diagram-mermaid. Access the skill through slash commands (e.g., /sf-diagram-mermaid) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.859 reviews
  • Charlotte Sanchez· Dec 12, 2024

    sf-diagram-mermaid has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chinedu Farah· Dec 12, 2024

    Useful defaults in sf-diagram-mermaid — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Dev Martin· Dec 12, 2024

    Solid pick for teams standardizing on skills: sf-diagram-mermaid is focused, and the summary matches what you get after install.

  • Li Patel· Dec 8, 2024

    sf-diagram-mermaid reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Diya Perez· Dec 8, 2024

    sf-diagram-mermaid fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Shikha Mishra· Dec 4, 2024

    We added sf-diagram-mermaid from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Emma Menon· Dec 4, 2024

    We added sf-diagram-mermaid from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Diya Choi· Nov 27, 2024

    We added sf-diagram-mermaid from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Yash Thakker· Nov 23, 2024

    sf-diagram-mermaid reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Diya Lopez· Nov 23, 2024

    sf-diagram-mermaid reduced setup friction for our internal harness; good balance of opinion and flexibility.

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