Ruflo is an execution and coordination layer for Claude Code and Codex that equips AI coding agents with tools, memory, control loops, sandboxes, and collaboration mechanisms. Developers use it to organize specialized agents into swarms, coordinate workflows, retain knowledge across sessions, and communicate across machines. The catalogue entries are Ruflo’s skills, commands, agents, hooks, and plugin components.
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.
git clone --depth 1 https://github.com/ruvnet/rufloWrote 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/commands/ruvnet/ruflo/swarm)<a href="https://agentmods.dev/commands/ruvnet/ruflo/swarm"><img src="https://agentmods.dev/badge/commands/ruvnet/ruflo/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/commands/ruvnet/ruflo/swarm"><img src="https://agentmods.dev/badge/commands/ruvnet/ruflo/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 | $0.00013 | $0.00618 |
| Opus 5.5 | $0.00005 | $0.00247 |
| Sonnet 5.5 | $0.00003 | $0.00124 |
| Haiku 4.5 | $0.00001 | $0.00062 |
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 1mo 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- flow-nexus-swarm — 100% identical, 0 lines differ
- flow-nexus-swarm — 100% identical, 0 lines differ
- flow-nexus-swarm — 100% identical, 0 lines differ
- flow-nexus-swarm — 100% identical, 0 lines differ
- flow-nexus-swarm — 100% identical, 91 lines differ
- flow-nexus-swarm — 100% identical, 0 lines differ
- swarm — 100% identical, 137 lines differ
- flow-nexus-swarm — 100% identical, 0 lines differ
What it actually says
Flow Nexus Swarms
Deploy and manage AI agent swarms in the cloud.
Initialize Swarm
mcp__flow-nexus__swarm_init({
topology: "hierarchical", // mesh, ring, star, hierarchical
maxAgents: 8,
strategy: "balanced" // balanced, specialized, adaptive
})
Spawn Agents
mcp__flow-nexus__agent_spawn({
type: "researcher", // coder, analyst, optimizer, coordinator
name: "Lead Researcher",
capabilities: ["web_search", "analysis", "summarization"]
})
Orchestrate Tasks
mcp__flow-nexus__task_orchestrate({
task: "Build a REST API with authentication",
strategy: "parallel", // parallel, sequential, adaptive
maxAgents: 5,
priority: "high"
})
Monitor Swarm
// Get swarm status
mcp__flow-nexus__swarm_status()
// List active swarms
mcp__flow-nexus__swarm_list({ status: "active" })
// Scale swarm
mcp__flow-nexus__swarm_scale({ target_agents: 10 })
// Destroy swarm
mcp__flow-nexus__swarm_destroy({ swarm_id: "id" })
Templates
// Use pre-built swarm template
mcp__flow-nexus__swarm_create_from_template({
template_name: "full-stack-dev",
overrides: {
maxAgents: 6,
strategy: "specialized"
}
})
// List available templates
mcp__flow-nexus__swarm_templates_list({
category: "quickstart" // specialized, enterprise, custom
})
Common Swarm Patterns
Research Swarm
mcp__flow-nexus__swarm_init({ topology: "mesh", maxAgents: 5 })
mcp__flow-nexus__agent_spawn({ type: "researcher", name: "Lead" })
mcp__flow-nexus__agent_spawn({ type: "analyst", name: "Data Analyst" })
mcp__flow-nexus__task_orchestrate({ task: "Research ML trends" })
Development Swarm
mcp__flow-nexus__swarm_init({ topology: "hierarchical", maxAgents: 8 })
mcp__flow-nexus__agent_spawn({ type: "coordinator", name: "PM" })
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Backend Dev" })
mcp__flow-nexus__agent_spawn({ type: "coder", name: "Frontend Dev" })
mcp__flow-nexus__task_orchestrate({ task: "Build e-commerce platform" })
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.
- 1mo ago First seen · 87 lines · 13 tokens per session scan A c59562ffd4d9
flow-nexus-swarm is a command published in the GitHub repository ruvnet/ruflo (77,829 stars, last pushed today), licensed MIT. It adds 13 tokens to every session and 618 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other commands, from other repositories
briefing
Structured pre-execution briefing session -- collects case context through specialist panel, builds execution plan, supports resume and depth control.
legal-5step
Execute the BetterCallClaude 5-step Swiss legal framework: intake → research → strategy → adversarial → draft. A complete end-to-end pipeline for any Swiss legal matter, from document analysis through final legal output.
help
Show complete BetterCallClaude command reference, available agents, skills, and usage examples.
legal-goal
Define a checkable legal success condition for /legal-loop. Accepts a named profile (citations-clean, draft-passes-gate, adversarial-converge, nda-batch-clean, reg-watch, timeline-sourced) or free-text objective. Produces a persisted Goal Record — never starts work itself.
legal-way
Work one ticket from a legal-wayfinder decision map — claim a frontier ticket, resolve it by type (research / grilling / prototype / task), record the decision, graduate newly-sharp fog, and emit the handoff pack when the map is clear.
create-workflow
Create a reusable custom workflow by combining BetterCallClaude agents. Interview-based: pick agents, order them, define the output. Saved for future use with /bettercallclaude:workflow.