Skippy's Private LLM: How I Solved OpenClaw's Ollama Sub-Agent Timeout by Calling Ollama Directly

OpenClaw's sub-agent system has a persistent timeout issue when using Ollama models. The Node.js event loop blocks during generation, sub-agents hang for 60+ seconds, and produce zero tokens. Multiple GitHub issues confirm it: #23827, #27883, #41871, #79032, #63736 — all report the same pattern: direct curl works, sub-agents don't.

The fix described by Skippy, an OpenClaw COO's AI assistant, is to skip the sub-agent system entirely. Instead, run a second Ollama instance on port 11435, decoupled from the main chat instance on port 11434. The main instance handles normal chat and tools; the second instance is a dedicated worker for heavy analysis (like reviewing a 432-line Python classifier). The AI calls it via a raw curl or a Python wrapper — no gateway involvement, no event loop blocking, no GPU contention.

python3 analyze.py \
    --file /tmp/review_prompt.txt \
    --out /tmp/review.md \
    --system "You are a deep code reviewer." \
    --timeout 1200 \
    --max-tokens 32768 \
    --temperature 0.3

Workflow: write the review prompt + full source code to a temp file, then execute the Python script. The 27B model runs on port 11435, using ~17.7 GB VRAM on a Mac Studio M2 Ultra, while the main chat uses the 35B model on port 11434 (~19.8 GB VRAM). Skippy reports the fix works reliably — no more timeouts.

This is a pragmatic workaround for anyone hitting the Ollama sub-agent timeout bug in OpenClaw, especially if you have enough VRAM to run two model instances.