hive/examples/templates/job_hunter/README.md

Job Hunter

Version: 1.0.0 Type: Multi-node agent Created: 2026-02-13

Overview

Analyze a user's resume to identify their strongest role fits, find 10 matching job opportunities, let the user select which to pursue, then generate a resume customization list and cold outreach email for each selected job.

Architecture

Execution Flow

intake → job-search → job-review → customize

Nodes (4 total)

1. intake (event_loop)
   • Collect resume from user, analyze skills and experience, identify 2-3 strongest role types
   • Writes: resume_text, role_analysis
   • Client-facing: Yes (blocks for user input)
2. job-review (event_loop)
   • Present all 10 jobs to the user, let them select which to pursue
   • Reads: job_listings, resume_text
   • Writes: selected_jobs
   • Client-facing: Yes (blocks for user input)
3. customize (event_loop)
   • For each selected job, generate resume customization list and cold outreach email
   • Reads: selected_jobs, resume_text
   • Writes: application_materials
   • Tools: save_data
   • Client-facing: Yes (blocks for user input)
4. job-search (event_loop)
   • Search for 10 jobs matching identified roles and scrape job posting details
   • Reads: role_analysis
   • Writes: job_listings
   • Tools: web_search, web_scrape

Edges (3 total)

• intake → job-search (condition: on_success, priority=1)
• job-search → job-review (condition: on_success, priority=1)
• job-review → customize (condition: on_success, priority=1)

Goal Criteria

Success Criteria

Identifies 2-3 role types that genuinely match the user's experience (weight 0.2)

• Metric: role_match_accuracy
• Target: >=0.8 Found jobs align with identified roles and user's background (weight 0.2)
• Metric: job_relevance_score
• Target: >=0.8 Resume changes are specific, actionable, and tailored to each job posting (weight 0.25)
• Metric: customization_specificity
• Target: >=0.85 Cold emails are personalized, professional, and reference specific company/role details (weight 0.2)
• Metric: email_personalization_score
• Target: >=0.85 User approves outputs without major revisions needed (weight 0.15)
• Metric: approval_rate
• Target: >=0.9

Constraints

Only suggest roles the user is realistically qualified for - no aspirational stretch roles (quality)

• Category: accuracy Resume customizations must be truthful - enhance presentation, never fabricate experience (ethical)
• Category: integrity Cold emails must be professional and not spammy (quality)
• Category: tone Only customize for jobs the user explicitly selects (behavioral)
• Category: user_control

Required Tools

• save_data
• web_scrape
• web_search

MCP Tool Sources

hive_tools (stdio)

Hive tools MCP server

Configuration:

• Command: uv
• Args: ['run', 'python', 'mcp_server.py', '--stdio']
• Working Directory: tools

Tools from these MCP servers are automatically loaded when the agent runs.

Usage

Basic Usage

from framework.runner import AgentRunner

# Load the agent
runner = AgentRunner.load("exports/job_hunter")

# Run with input
result = await runner.run({"input_key": "value"})

# Access results
print(result.output)
print(result.status)

Input Schema

The agent's entry node intake requires:

Output Schema

Terminal nodes: customize

Version History

• 1.0.0 (2026-02-13): Initial release
  • 4 nodes, 3 edges
  • Goal: Job Hunter