A sophisticated management framework that enables an AI agent to function as a CEO, delegating execution and validation to specialized child agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ceo-delegation
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 ceo-delegation 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 CEO Delegation Skill?
The CEO Delegation skill is a high-level workflow designed for complex AI agent environments. Rather than attempting to execute every task personally, the agent adopts a managerial persona—focusing on requirement analysis, global coordination, and rigorous quality control. By leveraging this module within Openclaw Skills, the primary agent maintains high availability and responsiveness, even when handling resource-intensive or long-running tasks.
This skill enforces a professional hierarchy where the main agent spawns specific child sessions for different roles. It utilizes a strategic model selection policy, routing complex reasoning or coding tasks to high-performance models like Claude Opus, while offloading routine validation and file operations to efficient models like GLM-4.6. This approach ensures maximum reliability through a strict double-acceptance protocol, where the executor and the validator are always distinct entities.
CEO Delegation Skill Use Cases
- Orchestrating multi-feature software development where different components are built in parallel.
- Automating content production pipelines that require independent drafting, fact-checking, and final review.
- Executing long-running system maintenance or deployment tasks without blocking the main user interface.
- Implementing high-reliability workflows where every output must pass a secondary AI inspection before delivery.
How CEO Delegation Skill Works
- The agent receives a user request and uses memory_search to find relevant success patterns from past experiences.
- It analyzes the resource requirements; if a task is expected to take longer than 30 seconds, it triggers the delegation protocol.
- A child agent is initialized via sessions_spawn, selecting the optimal LLM based on the task category (e.g., Opus for logic, GLM for configuration).
- The manager agent monitors progress every 60 seconds using sessions_list and sessions_history, providing a formatted heartbeat report to the user.
- Once the executor finishes, a separate validator agent is spawned to conduct an independent audit against the project requirements.
- After successful validation, the final result is delivered, and the session logic is archived into long-term memory for future RAG retrieval.
CEO Delegation Skill Setup
To integrate this workflow into your agent, ensure you have the Openclaw Skills framework installed and the session management tools enabled.
# Enable session and memory tools in your environment
openclaw skill add ceo-delegation
Configure your model aliases in your agent's profile to allow the CEO to route tasks effectively. Define opus for high-reasoning tasks and glm for utility and validation tasks to optimize for both quality and cost.
CEO Delegation Skill Data Schema & Taxonomy
The skill organizes data across active sessions and permanent memory to ensure continuity and traceability.
| Data Object | Storage | Purpose |
|---|---|---|
| Experience Logs | Long-term Memory | Stores RAG-indexed summaries of successful and failed delegations. |
| Session Labels | Session Metadata | Identifies the role of child agents (e.g., executor, reviewer). |
| Execution History | Session Store | Provides a granular audit trail of all commands run by child agents. |
| Progress Templates | Internal State | Standardized reporting structure for real-time user updates. |
CEO Delegation Skill Advanced Features
- Intelligent Model Routing: Automatically matches task complexity to the most cost-effective LLM.
- Parallel Multi-Agent Support: Spawns and manages multiple specialized agents simultaneously for high-throughput workflows.
- Guardrail Enforcement: Prevents main-thread blocking by strictly offloading any task exceeding 30 seconds to background sessions.
- Double-Blind Acceptance: Mandates that the validator agent must be different from the executor agent to minimize hallucination and error.
- Automated Heartbeat Reporting: Provides consistent, transparent progress updates without requiring manual status checks from the user.
SKILL.md
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