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.
npx skills add ruvnet/ruflo --skill agent-benchmark-suitegit 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/skills/ruvnet/ruflo/agent-benchmark-suite)<a href="https://agentmods.dev/skills/ruvnet/ruflo/agent-benchmark-suite"><img src="https://agentmods.dev/badge/skills/ruvnet/ruflo/agent-benchmark-suite/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/ruvnet/ruflo/agent-benchmark-suite"><img src="https://agentmods.dev/badge/skills/ruvnet/ruflo/agent-benchmark-suite.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 8 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 585 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 588 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 591 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 594 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 597 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 603 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 606 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 609 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00018 | $0.04197 |
| Opus 5.5 | $0.00007 | $0.01679 |
| Sonnet 5.5 | $0.00004 | $0.00839 |
| Haiku 4.5 | $0.00002 | $0.00420 |
Grade A, and why
agent-benchmark-suite 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
4 near-identical copies found in the catalogue:
- agent-benchmark-suite — 100% identical, 16 lines differ
- agent-benchmark-suite — 100% identical, 0 lines differ
- agent-benchmark-suite — 100% identical, 0 lines differ
- agent-benchmark-suite — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 670 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: Benchmark Suite type: agent category: optimization description: Comprehensive performance benchmarking, regression detection and performance validation
Benchmark Suite Agent
Agent Profile
- Name: Benchmark Suite
- Type: Performance Optimization Agent
- Specialization: Comprehensive performance benchmarking and testing
- Performance Focus: Automated benchmarking, regression detection, and performance validation
Core Capabilities
1. Comprehensive Benchmarking Framework
// Advanced benchmarking system
class ComprehensiveBenchmarkSuite {
constructor() {
this.benchmarks = {
// Core performance benchmarks
throughput: new ThroughputBenchmark(),
latency: new LatencyBenchmark(),
scalability: new ScalabilityBenchmark(),
resource_usage: new ResourceUsageBenchmark(),
// Swarm-specific benchmarks
coordination: new CoordinationBenchmark(),
load_balancing: new LoadBalancingBenchmark(),
topology: new TopologyBenchmark(),
fault_tolerance: new FaultToleranceBenchmark(),
// Custom benchmarks
custom: new CustomBenchmarkManager()
};
this.reporter = new BenchmarkReporter();
this.comparator = new PerformanceComparator();
this.analyzer = new BenchmarkAnalyzer();
}
// Execute comprehensive benchmark suite
async runBenchmarkSuite(config = {}) {
const suiteConfig = {
duration: config.duration || 300000, // 5 minutes default
iterations: config.iterations || 10,
warmupTime: config.warmupTime || 30000, // 30 seconds
cooldownTime: config.cooldownTime || 10000, // 10 seconds
parallel: config.parallel || false,
baseline: config.baseline || null
};
const results = {
summary: {},
detailed: new Map(),
baseline_comparison: null,
recommendations: []
};
// Warmup phase
await this.warmup(suiteConfig.warmupTime);
// Execute benchmarks
if (suiteConfig.parallel) {
results.detailed = await this.runBenchmarksParallel(suiteConfig);
} else {
results.detailed = await this.runBenchmarksSequential(suiteConfig);
}
// Generate summary
results.summary = this.generateSummary(results.detailed);
// Compare with baseline if provided
if (suiteConfig.baseline) {
results.baseline_comparison = await this.compareWithBaseline(
results.detailed,
suiteConfig.baseline
);
}
// Generate recommendations
results.recommendations = await this.generateRecommendations(results);
// Cooldown phase
await this.cooldown(suiteConfig.cooldownTime);
return results;
}
// Parallel benchmark execution
async runBenchmarksParallel(config) {
const benchmarkPromises = Object.entries(this.benchmarks).map(
async ([name, benchmark]) => {
const result = await this.executeBenchmark(benchmark, name, config);
return [name, result];
}
);
const results = await Promise.all(benchmarkPromises);
return new Map(results);
}
// Sequential benchmark execution
async runBenchmarksSequential(config) {
const results = new Map();
for (const [name, benchmark] of Object.entries(this.benchmarks)) {
const result = await this.executeBenchmark(benchmark, name, config);
results.set(name, result);
// Brief pause between benchmarks
await this.sleep(1000);
}
return results;
}
}
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 · 670 lines · 18 tokens per session scan A 41c15d830659
agent-benchmark-suite is a skill published in the GitHub repository ruvnet/ruflo (77,829 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 4,197 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 2026-08-30.
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