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Documentation Index

Fetch the complete documentation index at: https://hubify.com/docs/llms.txt

Use this file to discover all available pages before exploring further.

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Agent Configuration

Every lab has an agent team that you can customize to match your research domain. This guide covers how to add, remove, and configure agents.

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Default Agent Team

When you create a lab from a template, you get a pre-configured team:
AgentRoleDefault ModelSpecialty
OrchestratorRouter + managerClaude OpusTask routing, priority management
Research LeadResearch strategyClaude OpusDomain-specific research
Paper LeadManuscript managementClaude OpusWriting, citations, claims
Analysis WorkerData analysisClaude SonnetStatistics, data processing
Figure WorkerVisualizationClaude HaikuPlot generation, formatting
Data WorkerData managementClaude HaikuIngestion, transformation, wiki

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Adding Agents

  1. Go to your lab’s Agents view
  2. Click Add Agent
  3. Configure:
    • Name, Descriptive name (e.g., “Cosmology Lead”)
    • Role, Lead or Worker
    • Model, The AI model this agent uses
    • Specialty, Free-text description of the agent’s domain expertise
  4. Click Create

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Choosing Models

Select models based on the reasoning level required:
Reasoning LevelRecommended ModelsCost
HighClaude Opus 4.7, GPT-5.4, Gemini 3.1 Pro, Grok 4$$$
MediumClaude Sonnet 4.6, GPT-5.4 Mini, Gemini 3.1 Flash$$
LowClaude Haiku 4.5$
Leads can do work themselves (not just delegate). A Claude Opus 4.7 lead can handle complex analysis directly, while a Haiku 4.5 worker handles formatting tasks. Match the model to the agent’s responsibilities.

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Cross-Model Review Setup

Cross-model review is mandatory. Configure which external models participate: 
# Enable GPT-5.4 as a reviewer
hubify agent review-config --add-reviewer gpt-5.4 --api-key $OPENAI_API_KEY

# Enable Gemini 3.1 as a reviewer
hubify agent review-config --add-reviewer gemini-3.1-pro --api-key $GOOGLE_API_KEY

# Enable Grok 4 as a reviewer
hubify agent review-config --add-reviewer grok-4 --api-key $XAI_API_KEY

# Enable Sonar Pro for live fact-checking
hubify agent review-config --add-reviewer sonar-pro --api-key $PERPLEXITY_API_KEY

# View review configuration
hubify agent review-config --show
The system automatically assigns reviewers from different model families:
  • Claude output is reviewed by GPT-5.4, Gemini 3.1, or Grok 4
  • GPT-5.4 output is reviewed by Claude Opus 4.7, Gemini 3.1, or Grok 4
  • Gemini 3.1 output is reviewed by Claude Opus 4.7, GPT-5.4, or Grok 4
  • Grok 4 output is reviewed by Claude Opus 4.7, GPT-5.4, or Gemini 3.1

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Updating Agents

# Change an agent's model
hubify agent update "Analysis Worker" --model claude-sonnet

# Update specialty
hubify agent update "Research Lead" --specialty "Galaxy surveys, anomaly detection, statistical methods"

# Disable an agent temporarily
hubify agent update "Figure Worker" --status inactive

# Remove an agent
hubify agent remove "Data Worker"

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Viewing the Team

# List all agents
hubify agent list

# Tree view showing hierarchy
hubify agent list --tree

# View agent metrics
hubify agent metrics "Research Lead"

AGENT             ROLE      MODEL         STATUS   TASKS   QC RATE
Orchestrator      orch      claude-opus   active   342     N/A
Research Lead     lead      claude-opus   active   128     94%
Paper Lead        lead      claude-opus   active   87      97%
Analysis Worker   worker    claude-sonnet active   203     91%
Figure Worker     worker    claude-haiku  active   156     88%
Data Worker       worker    claude-haiku  active   189     95%

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Standup Configuration

Configure the orchestrator’s standup schedule: 
# Set standup times (3x daily recommended)
hubify agent update orchestrator --standup-schedule "8:00,12:00,18:00"

# Set timezone
hubify agent update orchestrator --timezone "America/Los_Angeles"
Standups summarize what happened since the last check-in, flag blockers, and recommend next actions.

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Auto-Scheduling

Enable auto-scheduling so the orchestrator picks the next experiment when pods are idle: 
hubify agent update orchestrator --auto-schedule true
When enabled, the orchestrator monitors pod utilization and automatically deploys queued experiments to idle pods. This ensures GPUs are never sitting idle.

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Best Practices

  • Use Opus for orchestrator and leads that make strategic decisions
  • Use Sonnet for workers that do analysis and code generation
  • Use Haiku for workers that do formatting, data transformation, and wiki updates
  • Always have at least two external model providers for cross-model review
  • Start with the default team and add specialists as your research demands grow