by composo-ai · MCP Server · ★ 70
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git clone https://github.com/composo-ai/DishwasherBench.gitTaken 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 | 70 |
| Forks | 3 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65/100 |
| Open Issues | 48 |
| Last Updated | 2026-10-17 |
| Created | 2026-10-12 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~21k |
DishwasherBench DishwasherBench is a dishwasher-loading game on a physical simulation of a real machine, built to benchmark language models and playable by people in a browser. The game inside is called Spotless, and the packages are named . A player loads a 3D model of a Bosch SMV4HAX40G with rigid-body physics.
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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: