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 naveedharri/benai-skills --skill infographic-v2git clone --depth 1 https://github.com/naveedharri/benai-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/naveedharri/benai-skills/infographic-v2)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/infographic-v2"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/infographic-v2/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/naveedharri/benai-skills/infographic-v2"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/infographic-v2.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 46 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 47 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Excessive Agency · line 106 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Memory Poisoning · line 544 Skill injects content designed to persist in agent memory or context across interactions. Persistent injection can alter agent behavior long after the initial interaction.Fix: Do not allow untrusted input to persist in agent memory or context. Validate all content before storing and implement memory isolation between sessions.
- medium Memory Poisoning · line 548 Skill injects content designed to persist in agent memory or context across interactions. Persistent injection can alter agent behavior long after the initial interaction.Fix: Do not allow untrusted input to persist in agent memory or context. Validate all content before storing and implement memory isolation between sessions.
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 | $0.06243 |
| Opus 5 | $0.00041 | $0.03121 |
| Sonnet 5 | $0.00016 | $0.01249 |
| Haiku 4.5 | $0.00008 | $0.00624 |
Grade A, and why
infographic-v2 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 — 653 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Infographic Generator
Create professional infographics in the BenAI brand style for LinkedIn and newsletters. Uses Gemini AI via the Nano Banana MCP server for image generation.
Connectors: Nano Banana MCP (Gemini AI image generation)
Core philosophy: The quality of the output is determined by the quality of the thinking BEFORE any prompt is written. Spend 70% of the effort understanding what to visualize and 30% on how to visualize it.
UX philosophy: Every user interaction must be a genuine taste decision. If the AI can make a good default, it should make it silently and let the user override. Never ask for confirmation of something the AI decided.
When This Skill Loads
DO NOT load any reference files yet. Files load lazily, one phase at a time.
- Execute Phase 0 (silent config check)
- If API key is NOT configured: skip to Phase 5 (API Key Setup). Do NOT ask about content.
- If API key IS configured: begin Phase 1.
UNDERSTAND
Phase 0: Silent Config Check
Run silently. Do NOT ask questions yet.
0.1: Ensure Directory Structure
mkdir -p .infographic/images
mkdir -p .infographic/prompts
0.2: Check for API Key
if [ -n "$GEMINI_API_KEY" ]; then
echo "API key found in environment"
elif [ -f .env ] && grep -q "^GEMINI_API_KEY=.\+" .env; then
echo "API key found in .env file"
else
echo "API key not configured"
fi
Decision:
- Found (env var OR .env): proceed silently to Phase 1
- NOT found: jump IMMEDIATELY to Phase 5 (API Key Setup)
0.3: Check for Brand Config
Check these locations in order (first found wins):
if [ -f ./branding.md ]; then
cat ./branding.md
elif [ -f .infographic/brand.md ]; then
cat .infographic/brand.md
fi
If brand config exists, acknowledge briefly: "I found your brand context. Ready to create your infographic!"
How branding.md gets created: The /ads-creative skill collects brand info (colors, fonts, voice, audience) and writes ./branding.md in the project root. If the user has run an ads creative audit, this file will already exist. The infographic skill uses it for on-brand color palettes, typography, and style anchors.
What ships with it
6 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.
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 · 653 lines · 81 tokens per session scan A 176105a7a8b2
infographic-v2 is a skill published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 8d ago), licensed MIT. It adds 81 tokens to every session and 6,243 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.
Other skills, from other repositories
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A renderer that turns presentation content into a single HTML slide deck that opens directly in a browser. It creates a 16:9 slide sequence with navigation, fullscreen viewing, printing to PDF, and speaker-note controls.
media-audio-gen
An audio-generation skill for turning text into speech, cloning a voice from a sample, dubbing videos into other languages, and creating sound effects.
media-higgsfield-explainer
A Higgsfield workflow for making non-photorealistic narrated explainer videos. It pairs each narration line with a 10-second animated clip and joins the clips into one finished video.
media-higgsfield-identity
A Higgsfield workflow for keeping a person, character, product, or other visual reference consistent across generated images. It chooses between a trained identity model and a one-image reference method.
media-notebooklm-slide-prompt
A prompt builder that turns lecture, class, or seminar notes into instructions for NotebookLM Studio to create slides. It also creates image prompts for each slide using Nano Banana, Google's image-generation model.
design-logo
A brand-aware logo design workflow that reads a project's visual rules, chooses a logo type, and prepares a vector or symbol-based logo request.