Awesome-openclaw-skills pi-orchestration
Orchestrate multiple AI models (GLM, MiniMax, etc.) as workers using Pi Coding Agent with Claude as coordinator.
install
source · Clone the upstream repo
git clone https://github.com/sundial-org/awesome-openclaw-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/pi-orchestration" ~/.claude/skills/sundial-org-awesome-openclaw-skills-pi-orchestration && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/sundial-org/awesome-openclaw-skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/pi-orchestration" ~/.openclaw/skills/sundial-org-awesome-openclaw-skills-pi-orchestration && rm -rf "$T"
manifest:
skills/pi-orchestration/SKILL.mdsource content
Pi Orchestration
Use Claude as an orchestrator to spawn and coordinate multiple AI model workers (GLM, MiniMax, etc.) via Pi Coding Agent.
Supported Providers
| Provider | Model | Status |
|---|---|---|
| GLM | glm-4.7 | ✅ Working |
| MiniMax | MiniMax-M2.1 | ✅ Working |
| OpenAI | gpt-4o, etc. | ✅ Working |
| Anthropic | claude-* | ✅ Working |
Setup
1. GLM (Zhipu AI)
Get API key from open.bigmodel.cn
export GLM_API_KEY="your-glm-api-key"
2. MiniMax
Get API key from api.minimax.chat
export MINIMAX_API_KEY="your-minimax-api-key" export MINIMAX_GROUP_ID="your-group-id" # Required for MiniMax
Usage
Direct Commands
# GLM-4.7 pi --provider glm --model glm-4.7 -p "Your task" # MiniMax M2.1 pi --provider minimax --model MiniMax-M2.1 -p "Your task" # Test connectivity pi --provider glm --model glm-4.7 -p "Say hello"
Orchestration Patterns
Claude (Opus) can spawn these as background workers:
Background Worker
bash workdir:/tmp/task background:true command:"pi --provider glm --model glm-4.7 -p 'Build feature X'"
Parallel Army (tmux)
# Create worker sessions tmux new-session -d -s worker-1 tmux new-session -d -s worker-2 # Dispatch tasks tmux send-keys -t worker-1 "pi --provider glm --model glm-4.7 -p 'Task 1'" Enter tmux send-keys -t worker-2 "pi --provider minimax --model MiniMax-M2.1 -p 'Task 2'" Enter # Check progress tmux capture-pane -t worker-1 -p tmux capture-pane -t worker-2 -p
Map-Reduce Pattern
# Map: Distribute subtasks to workers for i in 1 2 3; do tmux send-keys -t worker-$i "pi --provider glm --model glm-4.7 -p 'Process chunk $i'" Enter done # Reduce: Collect and combine results for i in 1 2 3; do tmux capture-pane -t worker-$i -p >> /tmp/results.txt done
Orchestration Script
# Quick orchestration helper uv run {baseDir}/scripts/orchestrate.py spawn --provider glm --model glm-4.7 --task "Build a REST API" uv run {baseDir}/scripts/orchestrate.py status uv run {baseDir}/scripts/orchestrate.py collect
Best Practices
- Task Decomposition: Break large tasks into independent subtasks
- Model Selection: Use GLM for Chinese content, MiniMax for creative tasks
- Error Handling: Check worker status before collecting results
- Resource Management: Clean up tmux sessions after completion
Example: Parallel Code Review
# Claude orchestrates 3 workers to review different files tmux send-keys -t worker-1 "pi --provider glm -p 'Review auth.py for security issues'" Enter tmux send-keys -t worker-2 "pi --provider minimax -p 'Review api.py for performance'" Enter tmux send-keys -t worker-3 "pi --provider glm -p 'Review db.py for SQL injection'" Enter # Wait and collect sleep 30 for i in 1 2 3; do echo "=== Worker $i ===" >> review.md tmux capture-pane -t worker-$i -p >> review.md done
Notes
- Pi Coding Agent must be installed:
npm install -g @anthropic/pi-coding-agent - GLM and MiniMax have generous free tiers
- Claude acts as coordinator, workers do the heavy lifting
- Combine with process tool for background task management