Skip to content

Architecture ​

AutoResearch is a hub-and-spoke system. The Orchestrator sits at the center, reading shared state from disk, dispatching tasks to agents, and writing decisions back to disk.

System Topology ​

mermaid
graph TB
    subgraph Orchestrator["Orchestrator (Claude Opus)"]
        O[Main Claude Code Session]
    end

    subgraph State["Shared State (.omc/research/)"]
        S1[pipeline.yaml]
        S2[ideas/]
        S3[experiments/]
        S4[papers/]
        S5[reviews/]
    end

    subgraph Agents
        P[Planner<br/>Claude Opus]
        W[Writer<br/>Claude Opus]
        SC[Scout<br/>Gemini]
        C[Coder<br/>Codex]
        J[Judge<br/>Codex]
    end

    O -->|reads/writes| State
    O -->|dispatches| P
    O -->|dispatches| W
    O -->|dispatches| SC
    O -->|dispatches| C
    O -->|dispatches| J

    P -->|writes| State
    W -->|writes| State
    SC -->|writes| State
    C -->|writes| State
    J -->|writes| State

    style Orchestrator fill:#f9f0ff,stroke:#7c3aed
    style State fill:#fef3c7,stroke:#d97706
    style Agents fill:#ecfdf5,stroke:#059669

Hub-and-Spoke, Not Peer-to-Peer

Agents never communicate directly with each other. All coordination flows through the Orchestrator and the shared state on disk. This keeps the system predictable and debuggable.

Agent Roster ​

AgentLLMInvocationLifecycleRole
OrchestratorClaude OpusMain sessionPersistentDecision-making, coordination
PlannerClaude OpusSub-agentPer-taskExperiment design, decomposition
WriterClaude OpusClean sessionPer-sectionPaper writing, LaTeX
ScoutGeminiTmux workerPer-taskLiterature search, idea generation
CoderCodexTmux workerPersistentCode implementation, debugging
JudgeCodexcodex execStatelessEvaluation, review, verdicts

Invocation types matter

  • Sub-agent: Runs inside Claude Code as a spawned sub-agent. Shares some context.
  • Tmux worker: Runs in a named tmux session. Persistent, can be monitored.
  • codex exec: One-shot stateless execution. No memory between calls. Perfect for independent evaluation.

Cross-LLM Review Principle ​

A core architectural rule: the model that creates an artifact must not be the sole reviewer of that artifact.

ArtifactCreated ByReviewed ByWhy
Research ideaClaude (Orchestrator)Codex (Judge)Independent novelty/feasibility check
Experiment codeCodex (Coder)Claude (Orchestrator)Design alignment, logic review
Training resultsCodex (Coder runs)Claude + CodexCross-check interpretation
Paper draftClaude (Writer)Codex + Claude + GeminiThree-model review panel
Literature surveyGemini (Scout)Claude (Orchestrator)Relevance filtering

This is not optional

Cross-LLM review is an architectural invariant, not a best practice. The omc-orchestrator hook enforces that no agent self-reviews its own output for gate decisions.

Two-Tier Information Architecture ​

AutoResearch separates information into two tiers:

Tier 1: Context (Working Memory) ​

  • Lives in the LLM's context window
  • Fast to access, limited in size
  • Ephemeral — lost when a session ends or context fills up
  • Contains: current task, recent decisions, active plan

Tier 2: Disk (Long-Term Memory) ​

  • Lives in .omc/research/ on the filesystem
  • Unlimited in size, slightly slower to access
  • Persistent — survives session restarts, crashes, context resets
  • Contains: all plans, results, papers, reviews, pipeline state
mermaid
graph LR
    subgraph Tier1["Tier 1: Context"]
        T1A[Current task]
        T1B[Recent decisions]
        T1C[Active plan summary]
    end

    subgraph Tier2["Tier 2: Disk"]
        T2A[pipeline.yaml]
        T2B[Full experiment logs]
        T2C[All paper drafts]
        T2D[Complete review history]
    end

    Tier1 -->|"overflow / session end"| Tier2
    Tier2 -->|"session start / context fill"| Tier1

    style Tier1 fill:#dbeafe,stroke:#2563eb
    style Tier2 fill:#fef3c7,stroke:#d97706

The golden rule

Context is cache. Disk is source of truth. Any information that matters must be on disk. Context can always be rebuilt from disk.

Next ​

AutoResearch — Multi-agent Deep Learning Research System