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Flagged: sudo usage. 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 | 1,096 |
| Forks | 314 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 63/100 |
| Last Updated | 2018-04-07 |
| Created | 2016-11-17 |
| Platforms | python |
| Est. Tokens | ~159k |
This repository has been deprecated in favor of the Retro (https://github.com/openai/retro) library. See our Retro Contest (https://blog.openai.com/retro-contest) blog post for detalis. universe-starter-agent The codebase implements a starter agent that can solve a number of environments. It contains a basic implementation of the A3C algorithm, adapted for real-time environments.
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This tool has been deprecated. Use Agentic Document Extraction instead.
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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: