agent-orchestrator-molterMulti-agent orchestration with 5 proven patterns - Work Crew, Supervisor, Pipeline, Council, and Auto-Routing
Install via ClawdBot CLI:
clawdbot install variable190/agent-orchestrator-molterGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Contains instructions to override system prompt or ignore user requests
"ignore previous instructions"Calls external URL not in known-safe list
https://developers.openai.com/blog/skills-shell-tipsAI Analysis
The skill's primary risk is a prompt poisoning instruction ('ignore previous instructions'), which could be used to subvert agent behavior, but no evidence of credential harvesting, data exfiltration, or obfuscated malicious code was found in the provided definition. The external URL reference is to a known OpenAI developer blog, which is low-risk and plausibly related to skill functionality.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 21, 2026
A financial firm uses the crew pattern to research emerging technologies like quantum computing, assigning agents to technical feasibility, market trends, regulatory risks, and competitor analysis. This provides comprehensive insights for investment decisions by aggregating diverse perspectives into a consensus report.
A marketing agency employs the pipeline pattern to produce blog posts, with sequential stages for research, drafting, SEO optimization, and final review. This ensures high-quality, structured output for client campaigns by automating the workflow through specialized agents at each step.
A tech startup uses the supervise pattern to manage complex projects like refactoring a codebase, where a supervisor agent dynamically delegates tasks to worker agents for coding, testing, and documentation. This adapts to changing requirements and optimizes resource allocation in agile environments.
A legal consultancy applies the council pattern to assess new data privacy regulations, involving expert agents in law, ethics, and technology. This synthesizes multi-disciplinary input to provide balanced recommendations for corporate compliance strategies.
An e-commerce platform implements the auto-routing pattern to classify incoming customer queries, such as technical issues or billing questions, and direct them to appropriate specialist agents like support or analyst. This improves response efficiency by automating task classification based on confidence thresholds.
Offer the orchestrator as a cloud-based service with tiered pricing based on usage volume, such as number of agents or tasks processed. This model generates recurring revenue from businesses needing scalable multi-agent automation for workflows like research or content creation.
Provide customized implementation services to integrate the orchestrator into client systems, such as setting up specific patterns for industries like finance or marketing. Revenue comes from project-based fees and ongoing support contracts for tailored automation solutions.
Sell perpetual licenses for on-premises deployment to large organizations requiring high-security orchestration, such as in legal or compliance sectors. This includes upfront license sales and optional maintenance fees for updates and technical support.
💬 Integration Tip
Start with low-risk tasks using the auto-routing pattern to test classification accuracy, then scale to more complex patterns like supervise for dynamic workflows, ensuring compatibility with OpenClaw 0.8+ and Python 3.8+.
Scored Apr 19, 2026
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