Openclaw Agents: Difference between revisions

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== HPCMATE Openclaw Agents  ==
== HPCMATE Openclaw Agents  ==
{| class="wikitable"
|+
!Agent Group
!Type
!Description
!Details
|-
|Baremetal System Configuration
|Orchestrator
|We use this agent to setup general purpose bare metal system configuration
Such as DLS(Deep Learning Station), AIS (AI Station) for each node
|TBD
|-
|Cluster Configuration
|
|We use this agent to setup a cluster master and slave for micro datacenter
|TBD
|-
|
|
|
|
|}


== Reference ==
== Reference ==
<references />
<references />

Revision as of 13:06, 3 June 2026

Type of Agents (Openclaw)

Comparison of Multiple Agent Configuration Strategies in OpenClaw[1]
Strategy Description Advantages Best Use Case
Strategy ①: Specialized Individual Agents (Library) Create separate .md files for each role, such as coder.md, tester.md, or reviewer.md. Simple to implement and very easy to manage individual roles. Quick, single-purpose tasks or simple automation.
Strategy ②: Orchestrator Pattern (Manager-Worker) A "Manager" agent analyzes the user's request and uses sessions_spawn to delegate sub-tasks to specific agents. High autonomy; can handle complex, multi-step reasoning without human intervention. Complex software development or multi-stage project management.
Strategy ③: Pipeline Configuration (Sequential) A chain of agents where the output of one agent serves as the input for the next (e.g., Scraper -> Analyzer -> Notifier). Provides a robust, automated workflow for continuous data processing. Automated monitoring, data extraction, and reporting pipelines.

HPCMATE Openclaw Agents

Agent Group Type Description Details
Baremetal System Configuration Orchestrator We use this agent to setup general purpose bare metal system configuration

Such as DLS(Deep Learning Station), AIS (AI Station) for each node

TBD
Cluster Configuration We use this agent to setup a cluster master and slave for micro datacenter TBD

Reference

  1. Generated by HPCMATE local AI