Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
ask-agents 1.0.1 - No file changes detected in this version. - No changes to features, instructions, or team structure. - Documentation and operational guidance remain the same as the previous release.
What This Skill Does
Teamo is a senior AI assistant for knowledge workers that handles task breakdown, planning, and delegation. It coordinates specialized sub-agents for research, data analysis, and writing using the McKinsey 7-Step Problem Solving Process. Each step in a complex task is assigned to the sub-agent best suited for that work type.
Rather than executing tasks directly, it acts as an orchestrating layer that assigns each sub-task to the most appropriate specialized agent, keeping costs predictable and preventing the context collapse that comes from a single agent handling everything.
When to use it
- Breaking a complex business decision into MECE sub-tasks
- Delegating deep market research to a specialized research sub-agent
- Routing data tables and code tasks to a dedicated analyst agent
- Retrieving internal knowledge base documents for a writing project
- Producing a structured decision report from multi-source research findings
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Analyze the competitive landscape for our product launch and produce a decision report.
- 1Defines the problem across 6 dimensions (description, decision maker, success criteria, constraints, accuracy) and confirms with user
- 2Calls Divide Agent to MECE-break the problem into two layers of sub-tasks
- 3Prioritizes sub-tasks by value, feasibility, and dependency order
- 4Delegates research sub-tasks to Research Team Leader with a structured instruction template covering scope, sources, and must-include points
- 5Calls chief_editor_desicion with all research reports and logs to produce the final storytelling report
A structured decision report with MECE breakdown, synthesized research findings, and final recommendations saved as a wiki document.