by Mybono · MCP Server · ★ 100
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/Mybono/ai-orchestrator ~/Projects/ai-orchestratorTaken from the project's README on GitHub.
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.
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 | 100 |
| Forks | 19 |
| Category | MCP Server |
| Quality Score | 71/100 |
| Last Updated | 2026-07-22 |
| Created | 2026-04-03 |
| Platforms | claude-code, cli, mcp |
| Est. Tokens | ~16k |
ai-orchestrator README · Architecture · Agents · Skills & Commands Portable AI developer setup: Claude thinks, local Ollama executes. Works with any project — TypeScript, Python, Flutter, Swift, C++. No Python dependency — all orchestration is pure Bash and . How it works triggers the full pipeline: Claude writes the plan. A local Ollama model writes the code. Claude reviews the output.
These tools work well together with ai-orchestrator for enhanced workflows:
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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: