The Agent Factory model represents a revolutionary approach to AI agent generation, with a workflow that can be divided into four intelligent phases:
- Requirements Analysis Phase: When a user enters a description such as 'Create an expert stock analysis agent', the system automatically extracts the key elements (timeframe, analysis dimensions, output requirements, etc.) through memory expansion and semantic analysis
- Tool selection phase: Intelligent matching of web crawlers, data analytics, report generation and other toolchains, such as the automatic combination of financial data APIs and visualization tools in the example
- Prompt Optimization Phase: The system automatically generates a structured Prompt containing elements such as task background, execution steps, output specifications, etc., which is more complete than a hand-written Prompt.
- Agent generation phase: The final result is a directly executable agent instance that can be tuned by the user via the edit-agent command.
Typical example: When inputting 'Analyze the stock trend of Xiaomi around May 22, 2024 and give trading recommendations', the system will automatically: 1) Configure the data acquisition tool 2) Set the time window 3) Add the technical indicator analysis module 4) Generate a report template with risk tips. The whole process is fully automated, eliminating the tedious process design and tool integration work in traditional development.
This answer comes from the articleCooragent: building a multi-intelligence task collaboration tool in one sentenceThe
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