AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
Open source AI agent policy enforcement. 80 policies. Two commands to install. Every evaluation under 10 ms. No telemetry. No account required.
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Developer toolsPython · ShellGitHub @vectimusOnlineOwner unconfirmed
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Deterministic governance for AI coding agents. Cedar-based policy engine that intercepts every agent action and evaluates it against deterministic rules before execution.
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Cedar policies for every AI agent action. Coding tools and agentic frameworks. Every evaluation under 10ms. Zero config.
That's it. Cedar policies evaluate every tool call - whether from a coding agent in your terminal or a framework agent in production. Dangerous commands, secret access, infrastructure changes and supply chain attacks blocked before execution.
Every policy references the real-world incident that motivated it. No "best practice" filler.
Maps to OWASP Agentic Top 10 (https://genai.owasp.org/resoRead the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
Cedar policies for every AI agent action. Coding tools and agentic frameworks. Every evaluation under 10ms. Zero config.
That's it. Cedar policies evaluate every tool call - whether from a coding agent in your terminal or a framework agent in production. Dangerous commands, secret access, infrastructure changes and supply chain attacks blocked before execution.
Every policy references the real-world incident that motivated it. No "best practice" filler.
Maps to OWASP Agentic Top 10 (https://genai.owasp.org/resoRead the full README ↗