Install
openclaw skills install mind-wanderBackground reasoning agent that autonomously explores open questions using a local LLM (Qwen3.5-9B), a private knowledge graph for dead-end tracking, and Perplexity web search. Fires on a schedule, picks one unresolved question from ON_YOUR_MIND.md, runs sandbox experiments and web searches, and writes findings to MENTAL_EXPLORATION.md only when genuinely novel — mirroring hippocampal background consolidation. Uses a separate FalkorDB 'wander' graph so exploration history never pollutes the primary agent context. Use when: setting up autonomous background research for an OpenClaw agent, exploring research questions without consuming primary LLM token budget, building training data from exploratory reasoning sessions, or tracking dead ends to avoid re-exploration. Triggers on: "mind wander", "background reasoning", "autonomous research", "wander agent", "ON_YOUR_MIND", "MENTAL_EXPLORATION", "dead ends", "explore while I sleep".
openclaw skills install mind-wanderAutonomous background reasoning agent. Runs locally on Qwen3.5-9B, consumes zero Anthropic tokens, and elevates findings to your context only when genuinely novel.
ON_YOUR_MIND.md → Qwen3.5 wander agent (every 30min)
open questions ↓ tools: query_graph, search_web,
tangents ↓ read_file, sandbox_run,
hypotheses ↓ check_dead_ends, record_dead_end, elevate()
↓
novelty gate (strict)
↙ ↘
MENTAL_EXPLORATION.md DEAD_ENDS.md + wander graph
(elevated findings) (closed threads, never in your context)
↓
memwatchd detects write
↓
graph-rag memory (your context)
ollama pull qwen3.5-wander-q8 (or use install script)# Install and set up
bash mind-wander/scripts/install.sh
# Write your first open question
echo "## What is the best approach to X?" >> ON_YOUR_MIND.md
# Run manually
python3 mind-wander/run.py --verbose
# Check findings
cat MENTAL_EXPLORATION.md
cat DEAD_ENDS.md
# Status
python3 mind-wander/run.py --status
Create ON_YOUR_MIND.md in your workspace root with questions and tangents.
The agent picks ONE per session. Format freely — the agent reads it as-is.
# On My Mind
## Open Questions
- Does X actually work better than Y in production?
- Is there a paper on Z that I haven't found yet?
## Tangents
- The implementation of A might connect to B in an interesting way
Mark completed items with ## ✅ COMPLETED so the agent skips them.
| Tool | Description |
|---|---|
query_graph | Search primary FalkorDB graph for related facts |
search_web | Perplexity AI web search |
read_file | Read workspace .md files |
list_files | List workspace .md files |
sandbox_run | Run Python snippets (numpy/scipy, no network, 30s limit) |
check_dead_ends | Check wander graph for previously closed threads |
record_dead_end | Record a closed thread (lower bar than elevate) |
elevate | Write finding to MENTAL_EXPLORATION.md (strict gate) |
Edit mind-wander/mind_wander_config.py:
WANDER_MODEL = "qwen3.5-wander-q8" # or q4 for lighter
WANDER_OLLAMA = "http://172.18.0.1:11436"
MAX_TOOL_CALLS = 20
COOLDOWN_HOURS = 3 # min hours before revisiting same anchor item
| File | Contents | In graph-rag? |
|---|---|---|
MENTAL_EXPLORATION.md | Elevated findings | ✅ via memwatchd |
DEAD_ENDS.md | Closed threads summary | ❌ never |
completions/wander/ | Full session JSON | ❌ training data only |
This skill produced the first novel finding in its 10-minute test run:
"Cross-space routing (routing in nomic-space, retrieving in arctic/bge-m3 space)
matches same-space baseline accuracy — suggesting domain routing is robust to
embedding space discontinuities." See NOVELTY_LOG.md for tracked findings.
See references/research.md for theoretical foundations and references/setup.md
for detailed installation instructions.