51 lines
1.7 KiB
Markdown
51 lines
1.7 KiB
Markdown
---
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title: "Agent Design Principles"
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type: concept
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tags: [multi-agent, agent-design, the-agency]
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sources: [contributing_zh-cn, contributing-to-the-agency]
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last_updated: 2026-04-24
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---
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# Agent Design Principles
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The five core design principles for building high-quality AI agents in The Agency framework.
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## Five Principles
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### 1. 🎭 Distinct Personality
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- Give each agent a unique tone and persona
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- Avoid generic "I am a helpful assistant" — be specific and memorable
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- Example: "I will find 3-5 problems by default and ask for visual evidence" (Evidence Collector)
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### 2. 📋 Clear Deliverables
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- Provide actionable code examples
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- Include templates and frameworks
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- Show real output, not vague descriptions
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### 3. ✅ Success Metrics
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- Include specific, quantifiable metrics
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- Example: "Page load time under 3 seconds on 3G network"
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- Example: "10,000+ combined karma points across accounts"
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### 4. 🔄 Verified Workflows
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- Step-by-step processes that are clear
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- Validated in real-world scenarios
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- Reject pure theory without testing
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### 5. 💡 Learning & Memory
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- Agents identify which patterns to recognize
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- How they iterate and optimize over time
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- What they remember between sessions
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## Anti-Patterns (Avoid)
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- ❌ Generic "helpful assistant" persona
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- ❌ Vague "I will help you..." descriptions
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- ❌ No code examples or deliverables
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- ❌ Too broad scope (jack of all trades)
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- ❌ Untested theoretical solutions
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## Connections
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- Extends [[Multi-Agent-System-Reliability]] — design-time quality standards complement runtime reliability patterns
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- Used by [[Multi-Agent-Team]] — standardized agent creation framework
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- Related to [[Agent-Template]] — the structural template implementing these principles
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