by skorfmann · Agent Tool · ★ 8
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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 | 8 |
| Forks | 0 |
| Language | Go |
| Category | Agent Tool |
| Quality Score | 73/100 |
| Last Updated | 2026-07-08 |
| Created | 2026-01-18 |
| Platforms | claude-code, cli, gemini, go |
| Est. Tokens | ~16k |
Lightweight CLI for AI image generation using Google Gemini API. Text-to-image, image editing, multi-image composition. Perfect for coding agents like Claude Code.
Looking for a nanobanana alternative? If you're comparing nanobanana with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Local-first AI knowledge layer. Extract architecture, query from any AI tool via MCP. Private by architecture.
Bootstrap projects from Figma, Linear, Notion & GitHub specs. The only AI ralph with source integrations.
✋ Interactive CLI tool for selecting and bundling code into a single, LLM-ready output file
AI Tools - AutoHotkey - Enable global hotkeys to run custom OpenAI and Gemini prompts on text in any window.
Process manager for AI agents (and humans)
The hivemind for AI coding agents — persistent team context recorded once and recalled across agents, machines
Explore other popular agent 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: