by chawlaaditya · AI Tool · ★ 61
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npx skills add chawlaaditya/NanoBananaASO
git clone https://github.com/chawlaaditya/NanoBananaASO.git "${CODEX_HOME:-$HOME/.codex}/skills/nano-banana-app-store-campaign"Taken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 61 |
| Forks | 2 |
| Language | Python |
| Category | AI Tool |
| Quality Score | 60/100 |
| Last Updated | 2026-03-31 |
| Created | 2026-03-29 |
| Platforms | python |
| Est. Tokens | ~14k |
Nano Banana ASO An agent skill for building premium, consistent App Store screenshot campaigns with Nano Banana Pro. This skill helps an agent: analyze an app codebase for brand, claims, and differentiators decide which app screens should be captured write a layout plan before image generation lock a style anchor for consistency across the set generate advertisement-first App Store slides...
These tools work well together with NanoBananaASO for enhanced workflows:
Looking for a NanoBananaASO alternative? If you're comparing NanoBananaASO with other ai tool tools, these 3 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Skip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights
Skill to talk to Claude about your projects over the phone
.NET MAUI skills for GitHub Copilot and Claude Code
Explore other popular ai tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: