No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Gloriaameng · Agent Tool · ★ 77
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is LLM-Agent-Harness-Survey safe to install? View the security audit →
English | 中文 Agent Harness for Large Language Model Agents: A Survey []() []() ⭐ This repo is actively maintained. If you find it useful, please star the repo to stay updated and help others find it. The agent execution harness — not the model — is the primary determinant of agent reliability at scale. This survey formalizes the harness as a first-class architectural object H = (E, T, C, S, L, V), surveys 110+ papers, blogs and reports across 23 systems, and maps 9 open technical challenges. 📄 Read the Paper 🌐 [Preprints Version (v3)](https://www.preprints.
| Stars | 77 |
| Forks | 0 |
| Category | Agent Tool |
| License | CC-BY-4.0 |
| Quality Score | 54.5308580135315/100 |
| Last Updated | 2026-04-14 |
| Created | 2026-04-03 |
| Est. Tokens | ~1862k |
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LLM-Agent-Harness-Survey is Survey on LLM agentharness engineering with a taxonomy. 110+ papers, 23 systems analyzed.. It is categorized as a Agent Tool with 77 GitHub stars.
You can find installation instructions and usage details in the LLM-Agent-Harness-Survey GitHub repository at github.com/Gloriaameng/LLM-Agent-Harness-Survey. The project has 77 stars and 0 forks, indicating an active community.
LLM-Agent-Harness-Survey is released under the CC-BY-4.0 license, making it free to use and modify according to the license terms.
The top alternatives to LLM-Agent-Harness-Survey on Agent Skills Hub include omnicoreagent, Autono, ai-agent-tools-catalog. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: