A command-driven interface for orchestrating isolated OpenClaw agents directly through chat shorthand.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-control
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agent-control using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Control?
Agent Control is a core utility designed for the Openclaw Skills ecosystem that translates intuitive chat commands into powerful CLI operations. It allows developers to manage the lifecycle of isolated agents without needing to memorize complex terminal syntax. By providing a bridge between the chat interface and the underlying OpenClaw engine, it ensures that workspace management remains fluid and integrated into the development conversation.
This skill is particularly valuable for power users who maintain multiple project contexts. It handles everything from agent creation and workspace assignment to identity management, ensuring that every interaction within your Openclaw Skills environment is routed to the correct execution context with minimal friction.
Agent Control Use Cases
- Creating new isolated workspaces for specific projects using Openclaw Skills.
- Rapidly switching between different agent contexts during multi-tasking sessions.
- Binding specific chat channels to dedicated agents to ensure task isolation.
- Monitoring active agent instances via the list command to manage system resources.
- Customizing agent appearances with unique emojis and avatars for better visual organization.
How Agent Control Works
- The user provides a shorthand command such as agent create or agent bind in the chat.
- The skill parses the input string to identify the action, agent name, and optional parameters like workspace paths or model IDs.
- The parsed request is mapped to the corresponding OpenClaw CLI execution pattern.
- For destructive actions like agent deletion, the skill triggers a safety check requiring explicit user confirmation.
- Upon execution, the skill provides a concise success or failure notification along with a suggested next command to maintain workflow momentum.
Agent Control Setup
To integrate this skill into your Openclaw Skills setup, ensure the OpenClaw CLI is accessible in your environment. No complex installation is required beyond placing the skill in your active directory.
# Verify OpenClaw CLI accessibility
openclaw agents list
# The skill will automatically map chat commands to this CLI
Agent Control Data Schema & Taxonomy
The Agent Control skill manages data through the standard OpenClaw agent registry. It organizes agent metadata using the following structure:
| Parameter | Type | Description |
|---|---|---|
| name | String | The unique identifier for the agent instance |
| workspace | Path | The filesystem directory isolated for the agent |
| model | ID | The specific LLM configuration used by the agent |
| identity | Object | Metadata containing display name, emoji, and avatar path |
| bindings | String | The channel or account ID associated with the agent |
Agent Control Advanced Features
- Context-aware channel routing to ensure Openclaw Skills are always executing in the correct environment.
- Dynamic identity updates allowing for real-time changes to agent display names and visual markers.
- Safety-first destructive workflows with mandatory confirmation loops for agent deletion.
- Deterministic command parsing via integrated Python helper scripts for high reliability.
- Automated workspace pathing that defaults to structured directory hierarchies for better organization.
SKILL.md
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