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PL Agent Orchestration
by
samledger67-dotcom
· GitHub ↗
· v1.0.0
· MIT-0
163
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Install in OpenClaw
/install pl-agent-orchestration
Description
Multi-agent orchestration patterns for production deployments. Covers sub-agent QC workflow, model staggering across 5+ models, cross-validation patterns, fa...
Usage Guidance
This skill is an instruction-only orchestration guide and appears internally consistent. Before using it: ensure your agent environment provides the necessary model API credentials (the SKILL does not request them), set quotas/limits to control cost, review privacy policies for every model provider you call (sensitive data will be sent to multiple third parties), test the patterns in a safe sandbox, and monitor/autopsy agent actions and billing when you enable autonomous runs.
Capability Analysis
Type: OpenClaw Skill
Name: pl-agent-orchestration
Version: 1.0.0
The skill bundle provides comprehensive documentation and architectural patterns for multi-agent orchestration, including quality control loops, model routing, and cost optimization. The provided Python examples and configuration snippets (SKILL.md) are educational and align with standard AI engineering practices without any evidence of malicious intent, data exfiltration, or unauthorized execution.
Capability Assessment
Purpose & Capability
The name and description match the SKILL.md content: it documents multi-agent orchestration, QC loops, model staggering, routing, and cost tradeoffs. All required resources referenced are models and orchestration patterns, which are appropriate for this purpose. There are no unrelated environment variables, binaries, or config paths requested.
Instruction Scope
SKILL.md contains patterns, examples, and pseudocode (call_model calls) that stay within orchestration and routing concerns. It does not instruct reading local files, scraping unrelated system state, or exfiltrating data to unknown endpoints. It does assume the availability of multiple model APIs, which is expected for this skill.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only, so nothing will be written to disk or installed by the skill itself.
Credentials
The skill declares no required env vars or credentials, which is reasonable for an instruction-only orchestration guide. In practice, using these patterns will require API keys/credentials for each model provider; that is expected but correctly left to the host environment rather than embedded in the skill.
Persistence & Privilege
always is false and the skill does not request persistent or elevated privileges or indicate it will modify other skills or system-wide settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install pl-agent-orchestration - After installation, invoke the skill by name or use
/pl-agent-orchestration - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Multi-agent orchestration patterns for production deployments
Metadata
Frequently Asked Questions
What is PL Agent Orchestration?
Multi-agent orchestration patterns for production deployments. Covers sub-agent QC workflow, model staggering across 5+ models, cross-validation patterns, fa... It is an AI Agent Skill for Claude Code / OpenClaw, with 163 downloads so far.
How do I install PL Agent Orchestration?
Run "/install pl-agent-orchestration" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is PL Agent Orchestration free?
Yes, PL Agent Orchestration is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does PL Agent Orchestration support?
PL Agent Orchestration is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created PL Agent Orchestration?
It is built and maintained by samledger67-dotcom (@samledger67-dotcom); the current version is v1.0.0.
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