Signal Sieve LinkedIn Agent - Resource Package
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This folder contains all the resources needed to build and test the Signal Sieve LinkedIn agent.

CONTENTS:
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1. Agent_Instruction_Block.txt
   - The complete system prompt for the Signal Sieve agent
   - Copy this entire file and paste it as the system instruction/prompt in your agent platform
   - This instruction block contains all the scenario detection logic, output formatting rules, and analysis requirements

2. Sample_Prompts.txt
   - Five copy/paste-ready sample prompts demonstrating different scenarios:
     * How do I use this agent?
     * HR Talent Outreach Review
     * Recruiter Outreach Comparison
     * Sales Enablement
     * Strategic Networking
   - Use these to test your agent after deployment

3. Demo_Files/ (folder)
   - Five sample messages.csv files representing different fictional recruiters:
     * hr_recruiter_messages_lisa_wang.csv
     * hr_recruiter_messages_michael_zhang.csv
     * hr_recruiter_messages_sarah_mitchell.csv
     * hr_recruiter_messages_jennifer_rodriguez.csv
     * hr_recruiter_messages_david_chen.csv
   - Each file represents a different recruiter's LinkedIn messaging history
   - Use these files to test the agent's analysis capabilities
   - Perfect for demonstrating the "Recruiter Outreach Comparison" scenario by uploading multiple files

HOW TO USE THE DEMO FILES:
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Single File Test:
- Upload one CSV file to test the "HR Talent Outreach Review" scenario
- The agent will analyze that recruiter's performance and provide coaching insights

Multiple File Test:
- Upload 2-5 CSV files to test the "Recruiter Outreach Comparison" scenario
- The agent will compare recruiters side-by-side with charts and tables

HOW TO CREATE MORE DEMO FILES:
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You can generate additional demo files using an AI assistant like Microsoft Copilot or Manus:

1. Upload one of the existing CSV files as a template
2. Describe the new recruiter persona you want to create
3. Use a prompt like:

   "Please create a new CSV file named 'hr_recruiter_messages_[new_name].csv' 
   that matches the exact formatting of the attached file.
   
   The new file should represent a recruiter named [New Name] who:
   - [Describe their role, e.g., 'Senior Technical Recruiter at a cybersecurity startup']
   - [Describe their specialty, e.g., 'Specializes in hiring Threat Intelligence Analysts']
   - [Describe their messaging style, e.g., 'Highly personalized, avoids templates, high reply rate']
   
   Generate 20-30 conversation entries over a two-month period with replies, 
   follow-ups, and scheduled calls."

4. Review and refine the generated file

DEPLOYMENT CHECKLIST:
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Before deploying your Signal Sieve agent, ensure:
- [ ] The full instruction block is set as the system prompt
- [ ] The agent can accept CSV file uploads
- [ ] The agent can execute Python code for data analysis and chart generation
- [ ] Scenario detection is working correctly
- [ ] Charts are rendering and embedding properly
- [ ] Multi-file uploads are handled correctly for the Comparison scenario

For full implementation details, see the main documentation file:
Signal_Sieve_LinkedIn_Agent_Documentation.docx

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Created by Manus AI for Ken, Sr. Director for Cloud Engineering at TD SYNNEX
AI Train-the-Trainer Workshop for Microsoft CSP Partners
February 09, 2026
