A sophisticated orchestration pattern for running multiple AI agents concurrently to solve independent technical problems without shared state interference.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dispatching-parallel-agents
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 dispatching-parallel-agents 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 Dispatching Parallel Agents?
The Dispatching Parallel Agents skill is a strategic methodology designed to scale AI-driven development by handling multiple unrelated failures or tasks simultaneously. Instead of investigating bugs or implementing features sequentially, this approach utilizes the Openclaw Skills framework to assign one agent per independent problem domain. This ensures that investigations into different subsystems, such as tool approval flows and abort functionality, happen in parallel.
By isolating domains, developers can leverage the full power of concurrent execution, ensuring that time is not wasted on serial processing when tasks have no shared dependencies. This skill transforms how complex debugging sessions are handled, allowing for a focused and highly efficient workflow that leverages Openclaw Skills to maintain high standards of code quality and speed.
Dispatching Parallel Agents Use Cases
- Managing multiple test files failing with distinct and unrelated root causes.
- Investigating independent subsystem failures following a large-scale codebase refactor.
- Executing non-dependent tasks like documentation updates and test fixes simultaneously.
- Scenarios where each problem domain can be understood without context from other ongoing investigations.
How Dispatching Parallel Agents Works
- Identify independent domains by grouping failures or tasks by their specific area of impact.
- Create focused agent tasks with a defined scope, clear goals, and explicit constraints to prevent overlap.
- Dispatch the agents in parallel using the Openclaw Skills concurrent execution pattern.
- Review the summaries and findings returned by each agent once their individual tasks are completed.
- Integrate all changes and perform a final full-suite test run to verify that no conflicts were introduced during parallel processing.
Dispatching Parallel Agents Setup
To begin using parallel dispatching with Openclaw Skills, ensure your environment supports concurrent task execution. Define your tasks clearly in your configuration or CLI:
# Example of dispatching parallel investigations
# Agent 1 focuses on abort logic
# Agent 2 focuses on batch processing
# Agent 3 focuses on race conditions
openclaw task "Fix agent-tool-abort.test.ts" &
openclaw task "Fix batch-completion-behavior.test.ts" &
openclaw task "Fix tool-approval-race-conditions.test.ts" &
wait
Dispatching Parallel Agents Data Schema & Taxonomy
The skill organizes its parallel operations using a structured metadata approach to ensure clarity and traceability:
| Attribute | Description |
|---|---|
| Task Scope | Defines the specific file or subsystem the agent is authorized to modify. |
| Constraints | Explicit instructions such as 'Do not change production code' to limit agent impact. |
| Input Context | Error messages, logs, or test names specific to the domain. |
| Return Schema | A structured summary of the root cause identified and the specific fixes applied. |
Dispatching Parallel Agents Advanced Features
- Multi-agent concurrency for massive reduction in debugging time.
- Domain isolation protocols to prevent agents from editing the same files simultaneously.
- Event-based synchronization to replace arbitrary timeouts in test fixes.
- Automated integration hooks to synthesize multiple agent outputs into a single pull request.
SKILL.md
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