Real-world AI agents that think, search, write, and build - powered by LangGraph and modular LLM
git clone https://github.com/nehalvaghasiya/langgraph-agents.gitReal-world AI agents that think, search, write, and build - powered by LangGraph and modular LLM
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/nehalvaghasiya/langgraph-agentsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create a LangGraph agent that can automate [TASK] for [COMPANY] in the [INDUSTRY] sector. The agent should use [DATA] to perform its functions. Specify the modules and workflow steps required to complete the task.
# LangGraph Agent Design for Market Analysis Automation ## Overview This agent automates market analysis for TechCorp in the technology sector using real-time industry data. It performs the following functions: - Data collection from multiple sources - Competitive analysis - Trend identification - Report generation ## Modules 1. **Data Collection Module**: Gathers data from APIs, web scraping, and internal databases 2. **Analysis Module**: Processes data to identify trends and competitive positioning 3. **Reporting Module**: Generates comprehensive market analysis reports 4. **Decision Support Module**: Provides actionable insights and recommendations ## Workflow 1. **Data Ingestion**: Collects and cleans data from specified sources 2. **Analysis**: Processes data to identify key trends and competitive insights 3. **Report Generation**: Compiles findings into a structured report 4. **Insight Delivery**: Presents actionable recommendations to stakeholders ## Expected Output - Comprehensive market analysis report - Identified trends and opportunities - Competitive positioning insights - Actionable recommendations for strategic decision-making
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