HexAgent Model Card
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HexAgent Model Card
| Field | Value |
|---|---|
| Repository | UnicomAI/hexagent |
| Category | LLM Computer Harness Runtime |
| Stars / forks snapshot | 122 / 12 |
| Language | Python |
| License | MIT |
| Raw capture | raw-github/unicomai_hexagent.md |
| Updated by | hourly public metadata update, 2026-05-27 16:00 +0800 |
1. Role in Self Evolve
HexAgent is a harness runtime that gives LLM agents an isolated computer layer and pluggable execution protocol instead of coupling agent runtime and machine state. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
runtime/computer separation -> pluggable local-vm-cloud computer protocol -> middleware hooks and skill injection -> isolated subagent execution with MCP/tool orchestration
3. Evidence Path
web-observed GitHub page showed 122 stars, 12 forks, 105 commits, MIT license, and README claims for runtime/computer isolation, pluggable Computer protocol, middleware pipeline, and skill discovery. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain LLM Computer Harness Runtime: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.