Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Orchestrates multiple Claude Code agents working in parallel on complex tasks. Agents coordinate through a shared task list, message each other directly, and own separate file boundaries to avoid conflicts. Includes templates for common patterns like multi-lens reviews, competing-hypothesis debugging, and full-stack feature builds.
Parallel agent execution cuts wall-clock time for independent workstreams that would otherwise be bottlenecked by a single context window working sequentially.
When to use it
- Running security, performance, and test reviews simultaneously on a PR
- Debugging a hard error by testing two competing root-cause theories in parallel
- Building a full-stack feature with separate agents for frontend, backend, and tests
- Generating an ADR through adversarial debate between architecture approaches
- Classifying or refactoring a large inventory of files in parallel
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Review this PR for security issues, performance regressions, and missing test coverage
- 1Enable CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1 in environment
- 2Select the parallel-review.md template
- 3Paste the spawn prompt into Claude Code via --pty
- 4Lead agent assigns security, performance, and test scopes to three separate teammates with explicit file boundaries
- 5Monitor progress with team-monitor.sh; wait for all teammates to complete before lead merges results
Three parallel reviews completed and consolidated into a single report covering security, performance, and test coverage
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.