DOS Kernel - trust substrate for agent fleets (stdio via PyPI)
@anthony-chaudhary
DOS Kernel - trust substrate for agent fleets (stdio via PyPI) について
Catch your AI agents when they lie about what they shipped — verifies claims against git instead of believing the agent.
基本情報
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概要
What is DOS Kernel - trust substrate for agent fleets (stdio via PyPI)?
DOS Kernel is a trust substrate for agent fleets that verifies agents' claims of shipped work against real-world artifacts—starting with git history. It runs as a referee via the dos CLI, installed as a single Python package (dos-kernel). It is built for teams running AI agents on code repos who need an objective verdict on whether work actually landed.
How to use DOS Kernel - trust substrate for agent fleets (stdio via PyPI)?
Install with pip install dos-kernel, then run dos init --hooks auto to wire into your existing agent runtime (e.g., Claude Code, Cursor) or dos quickstart for a throwaway demo. Use dos verify <plan> <phase> to check a claim against git commits: SHIPPED (exit 0) or NOT_SHIPPED (exit 1). The verdict can gate further actions in CI, MCP hosts, or fleet frameworks.
Key features of DOS Kernel - trust substrate for agent fleets (stdio via PyPI)?
- Verifies agent claims against git history, never the agent's narration.
- Detects silent collisions between agents racing on the same files.
- Flags spinning runs and saves compute by quitting doomed tasks.
- Works on any plain git repo with zero configuration.
- One runtime dependency: PyYAML (MIT license).
- Integrates via MCP, runtime hooks, CI, and fleet frameworks.
Use cases of DOS Kernel - trust substrate for agent fleets (stdio via PyPI)?
- Catching agents that falsely report shipping features (e.g., "login endpoint shipped" when no commit exists).
- Preventing silent file overwrites and collisions in multi-agent fleets.
- Saving fleet compute by automatically stopping runs that produce no landable work.
- Improving acceptance precision by rejecting unbacked claims before they pollute code.
FAQ from DOS
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