AIMDS

Community

Defend AI outputs with formal, fast defense.

Authorruvnet
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill helps you build production-grade AI manipulation defense systems by integrating Midstream's temporal analysis, AgentDB's vector search, and lean-agentic's formal verification to detect, analyze, and prove safety of AI-driven workflows, reducing risk, manual review time, and overall complexity.

Core Features & Use Cases

  • Temporal Analysis: Real-time detection of manipulation attempts using high-precision temporal tools.
  • Vector Intelligence: Rapid pattern matching and risk scoring with AgentDB.
  • Formal Verification: Theorem proving to ensure safety and policy compliance before actions.
  • Use Case: A security team deploys AIMDS to monitor an AI assistant, detect adversarial prompts, and block unsafe outputs while logging proofs for audits.

Quick Start

Create a new AIMDS project structure and install dependencies as described in the Quick Start section of the SKILL.md. Start the Midstream, AgentDB, and lean-agentic services, then feed a sample input to evaluate safety; review the result and the proof trace to confirm actions.

Dependency Matrix

Required Modules

temporal-comparetemporal-neural-solverstrange-loopnanosecond-schedulerquic-multistreamagentdblean-agenticzoddotenv

Components

scriptsreferences

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: AIMDS
Download link: https://github.com/ruvnet/midstream/archive/main.zip#aimds

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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