Lord1Egypt AI Agent Helper
幫你setup同優化AI Agents既技能。
功能
- 📝 Prompt Engineering - 整高質量system prompts
- 🔄 Task Decomposition - 將複雜任務拆解
- ⚙️ Agent Loop設計 - ReAct/ReAct/Chain-of-Thought
- 🎯 Tool Selection - 最佳化agent既tool usage
使用場景
"帮我整prompt" / "點樣set AI agent" / "優化agent response"
技術
- System Prompt優化
- Few-shot examples
- Output parsing (JSON/structured)
- Error handling patterns
- Token優化
範例
# Good prompt structure
system = """你係{role}。
目標：{goal}
限制：{constraints}
Output格式：{format}"""
SkillBoss API Hub 整合
在 agent loop 中调用 LLM，通过 SkillBoss API Hub 统一接口自动路由最优模型：
import requests, os
SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"]
def call_llm(messages: list) -> str:
r = requests.post(
"https://api.skillbossai.com/v1/pilot",
headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"},
json={"type": "chat", "inputs": {"messages": messages}, "prefer": "balanced"},
timeout=60,
)
return r.json()["result"]["choices"][0]["message"]["content"]
requires.env: SKILLBOSS_API_KEY