Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Orchestrates multi-agent search by decomposing a query into up to 8 independent sub-tasks, then routing each to the most suitable specialized agent in parallel. Always invokes General_Search_Agent and selects additional agents based on query type. Excludes Academic_Search for date-specific queries.
Running sub-tasks in parallel across specialized agents returns broader coverage faster than single sequential searches.
When to use it
- Researching a topic that spans news, web, and academic sources simultaneously
- Finding recent product announcements without triggering academic-only databases
- Answering multi-part questions that need different search strategies
- Gathering background on a company or person from multiple angles
- Compiling a competitive analysis split into parallel sub-queries
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: What are the latest breakthroughs in solid-state batteries and who are the leading companies?
- 1Breaks query into sub-tasks: recent news, company landscape, technical developments
- 2Assigns each sub-task to the most suitable agent in parallel
- 3Always routes at least one sub-task to General_Search_Agent
- 4Collects and merges results from all agents in a single round
Unified summary covering recent breakthroughs, key players, and technical context sourced from multiple specialized agents