Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add proffesor-for-testing/agentic-qe --skill flow-nexus-swarmgit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/flow-nexus-swarm)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/flow-nexus-swarm"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/flow-nexus-swarm/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/flow-nexus-swarm"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/flow-nexus-swarm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.04226 |
| Opus 5 | $0.00010 | $0.02113 |
| Sonnet 5 | $0.00004 | $0.00845 |
| Haiku 4.5 | $0.00002 | $0.00423 |
Grade A, and why
flow-nexus-swarm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to flow-nexus-swarm — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 611 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flow Nexus Swarm & Workflow Orchestration
Deploy and manage cloud-based AI agent swarms with event-driven workflow automation, message queue processing, and intelligent agent coordination.
📋 Table of Contents
- Overview
- Swarm Management
- Workflow Automation
- Agent Orchestration
- Templates & Patterns
- Advanced Features
- Best Practices
Overview
Flow Nexus provides cloud-based orchestration for AI agent swarms with:
- Multi-topology Support: Hierarchical, mesh, ring, and star architectures
- Event-driven Workflows: Message queue processing with async execution
- Template Library: Pre-built swarm configurations for common use cases
- Intelligent Agent Assignment: Vector similarity matching for optimal agent selection
- Real-time Monitoring: Comprehensive metrics and audit trails
- Scalable Infrastructure: Cloud-based execution with auto-scaling
Swarm Management
Initialize Swarm
Create a new swarm with specified topology and configuration:
mcp__flow-nexus__swarm_init({
topology: "hierarchical", // Options: mesh, ring, star, hierarchical
maxAgents: 8,
strategy: "balanced" // Options: balanced, specialized, adaptive
})
Topology Guide:
- Hierarchical: Tree structure with coordinator nodes (best for complex projects)
- Mesh: Peer-to-peer collaboration (best for research and analysis)
- Ring: Circular coordination (best for sequential workflows)
- Star: Centralized hub (best for simple delegation)
Strategy Guide:
- Balanced: Equal distribution of workload across agents
- Specialized: Agents focus on specific expertise areas
- Adaptive: Dynamic adjustment based on task complexity
Spawn Agents
Add specialized agents to the swarm:
mcp__flow-nexus__agent_spawn({
type: "researcher", // Options: researcher, coder, analyst, optimizer, coordinator
name: "Lead Researcher",
capabilities: ["web_search", "analysis", "summarization"]
})
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 611 lines · 20 tokens per session scan A f060e56109c5
flow-nexus-swarm is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (475 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 4,226 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to flow-nexus-swarm, differing in 0 lines, and is treated as a copy.
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