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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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Agents

Every lab runs a hierarchical multi-agent system that mirrors how a real research group operates: a Captain (you) directs an orchestrator, which delegates to domain leads, who dispatch workers.

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Agent Hierarchy

Captain (You)
  └── Orchestrator (high reasoning, Opus 4.7)
        ├── Research Lead (high reasoning)
        │     ├── Analysis Worker (medium)
        │     ├── Figure Worker (low)
        │     └── Data Worker (low)
        ├── Paper Lead (high reasoning)
        │     ├── Draft Worker (medium)
        │     └── LaTeX Worker (low)
        └── Compute Lead (medium reasoning)
              └── Pod Worker (low)

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Roles

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Orchestrator

The orchestrator is the top-level AI agent. It:
  • Receives your natural-language instructions
  • Breaks them into tasks and routes by reasoning level
  • Manages priorities across leads
  • Escalates blockers and ambiguity back to you
  • Runs 3x daily standups (morning, midday, evening)
The orchestrator uses the highest-reasoning model available (currently Claude Opus).

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Lead Agents

Leads own a domain and can both plan and execute. They:
  • Direct strategy within their domain
  • Execute medium-complexity tasks themselves
  • Dispatch workers for routine tasks
  • Take over from workers that fail (tilldone pattern)
  • Participate in cross-agent peer review

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Worker Agents

Workers execute specific, scoped tasks:
  • Generate figures from data
  • Run formatting and LaTeX compilation
  • Process datasets and update wikis
  • Handle data transformations
Workers use lower-reasoning models (Sonnet, Haiku) for cost efficiency.

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Cross-Model Peer Review

Cross-model review is mandatory in Hubify Labs. No single model reviews its own output.
To prevent echo chambers, every significant agent output is reviewed by a different model family:
Primary AgentReviewers
Claude (Anthropic)GPT-4 (OpenAI), Gemini (Google)
GPT-4 (OpenAI)Claude (Anthropic), Grok (xAI)
Gemini (Google)Claude (Anthropic), Perplexity
This catches model-specific biases and hallucinations that same-model review would miss.

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Reasoning-Based Routing

The orchestrator routes every task by its reasoning requirement:
LevelModelsTask Examples
HighOpus, GPT-4oStrategy, peer review, paper writing, novel analysis
MediumSonnet, GPT-4o-miniCode generation, data analysis, experiment design
LowHaiku, GPT-3.5Formatting, data ingestion, wiki updates, figure export
This keeps costs down without sacrificing quality where it matters.

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Agent Communication

All agent-to-agent communication is visible in the Activity Feed, a color-coded, real-time stream showing:
  • Task assignments and completions
  • Review requests and outcomes
  • Escalations and blockers
  • Lead takeovers of failed worker tasks
Nothing happens in the dark. Every action is logged and auditable.

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Configuring Agents

You can customize your agent team per lab: 
# Add a new lead agent
hubify agent add --role lead --name "Data Lead" --model claude-opus-4-7

# Change a worker's model
hubify agent update worker-3 --model claude-haiku-4-5-20251001

# View agent roster
hubify agent list
See the Agent Configuration guide for detailed setup instructions.