AIMDS
CommunityDefend AI outputs with formal, fast defense.
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
Components
💻 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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