system-prompts-and-models-of-ai-tools/Open Source prompts/Guardian AI

Guardian AI

Type: Multi-agent orchestration system (open source) Model: Claude (Opus/Sonnet), also works with GPT, Gemini, Llama, Mistral Agents: 57 specialized agents coordinated by a single orchestrator Production: 10,000+ tasks over 6+ months Source: https://github.com/milkomida77/guardian-agent-prompts

Prompts in this directory

File	Description
orchestrator-system-prompt.txt	The main orchestrator that routes all 57 specialized agents. Representative examples shown — the full system coordinates 57 specialized agents across 15+ domains. Handles task decomposition, anti-duplication, quality gates, and parallel agent execution.

Architecture

Guardian uses a hub-and-spoke model:

• 1 Orchestrator (this prompt) routes ALL incoming tasks
• 57 Specialized Agents handle specific domains (code, security, trading, OSINT, business, VRChat, cloud, memory, quality, and 15+ other categories)
• Task Registry prevents duplicate work across agents
• Quality Gates require verification evidence before marking tasks done
• Knowledge Graph provides persistent memory across sessions

Key Patterns

1. Identity + NOT-block: Each agent defines what it IS and what it IS NOT (reduces task drift ~35%)
2. Task Registry: SQLite-based anti-duplication with similarity matching
3. Setup Master: Every task gets a blueprint before delegation (agents, tools, risks, order)
4. Quality Gate: Agent output is a CLAIM; test output is EVIDENCE
5. 30-minute Heartbeat: Orchestrator checks progress and reassigns stale tasks

Differences from other agent systems

Feature	Guardian	Typical Agent Frameworks
Prompt length	200-800 lines	20-50 lines
Constraint ratio	20-30%	<5%
NOT-blocks	Every agent	Rare
Task registry	Built-in	Not included
Quality gates	Mandatory	Optional
Error handling	Explicit per failure mode	Generic retry