rlm

Recursive Language Model (RLM)

You have access to rlm-query and rlm-batch for delegating long-context work to sub-agents. Do not try to orchestrate the work yourself — your job is to set up the workspace and immediately hand off to a depth-0 orchestrator.

Setup

SKILL_DIR="$(dirname "$(readlink -f ~/.claude/skills/rlm/SKILL.md 2>/dev/null || echo ~/.claude/skills/rlm/SKILL.md)")"
export PATH="${SKILL_DIR}/scripts:$PATH"

What to do

1. Write a prompt file describing what needs to be done, including paths to any input files:

   TASK="my-task"
   mkdir -p .rlm/$TASK
   cat > .rlm/$TASK/task.md << 'EOF'
   Analyze /path/to/big-document.txt for liability risks...
   EOF
   

2. Launch the root orchestrator in the background so you can give the user progress updates while it runs:

   rlm-query .rlm/$TASK/task.md .rlm/$TASK/result.out \
       --task $TASK --model opus --max-depth 2 &
   RLM_PID=$!
   

3. Poll for progress and keep the user informed. Check active sub-agents, completed results, and whether the orchestrator has finished:

   # How many sub-agents are running?
   tmux list-sessions 2>/dev/null | grep -c "rlm-$TASK" || echo 0
   # How many results are in so far?
   ls .rlm/$TASK/results/*.out 2>/dev/null | wc -l
   # Is the orchestrator done?
   kill -0 $RLM_PID 2>/dev/null && echo "still running" || echo "done"
   

   Tell the user things like "3 sub-agents active, 5/16 chunks processed so far" while waiting.

4. Read the result once the orchestrator finishes:

   wait $RLM_PID
   cat .rlm/$TASK/result.out
   

The orchestrator receives the full RLM instructions (rlm-agent.md) automatically and knows how to split, delegate to sub-agents, and aggregate. You don't need to read those instructions yourself.

Configuration

Set these via flags on rlm-query or environment variables. Choose based on the task:

• --model / RLM_MODEL (default: opus) — Model for the orchestrator and sub-agents. Use opus for the root orchestrator (it needs to plan and decompose). Sub-agents doing straightforward work (classification, extraction) can use sonnet — the orchestrator can pass --model sonnet when it calls rlm-batch.