Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Jaganpro/sf-skills --skill sf-diagram-nanobananaprogit clone --depth 1 https://github.com/Jaganpro/sf-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jaganpro/sf-skills/sf-diagram-nanobananapro)<a href="https://agentmods.dev/skills/jaganpro/sf-skills/sf-diagram-nanobananapro"><img src="https://agentmods.dev/badge/skills/jaganpro/sf-skills/sf-diagram-nanobananapro/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jaganpro/sf-skills/sf-diagram-nanobananapro"><img src="https://agentmods.dev/badge/skills/jaganpro/sf-skills/sf-diagram-nanobananapro.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00081 | $0.01547 |
| Opus 5 | $0.00041 | $0.00773 |
| Sonnet 5 | $0.00016 | $0.00309 |
| Haiku 4.5 | $0.00008 | $0.00155 |
Grade A, and why
sf-diagram-nanobananapro scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- 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 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
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/architecture/integration-flow.md 1.1 KB
- assets/erd/core-objects.md 3.6 KB
- assets/erd/custom-objects.md 1.6 KB
- assets/lwc/dashboard-card.md 930 B
- assets/lwc/data-table.md 1.2 KB
- assets/lwc/record-form.md 1.1 KB
- assets/review/apex-review.md 1.1 KB
- assets/review/lwc-review.md 813 B
- CREDITS.md 2.3 KB
- README.md 3.1 KB
- references/architect-aesthetic-guide.md 8.8 KB
- references/examples-index.md 1.1 KB
- references/gemini-cli-setup.md 1.1 KB
- references/interview-questions.md 15 KB
- references/iteration-workflow.md 6.4 KB
- scripts/check-prerequisites.sh 4.1 KB runs code
- scripts/generate_image.py 7.5 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 199 lines · 81 tokens per session scan A 90e9fe6bcda8
sf-diagram-nanobananapro is a skill published in the GitHub repository Jaganpro/sf-skills (423 stars, last pushed 4mo ago), licensed MIT. It adds 81 tokens to every session and 1,547 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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