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 henryalouf/ruflow --skill agent-performance-monitorgit clone --depth 1 https://github.com/henryalouf/ruflowWrote 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/henryalouf/ruflow/agent-performance-monitor)<a href="https://agentmods.dev/skills/henryalouf/ruflow/agent-performance-monitor"><img src="https://agentmods.dev/badge/skills/henryalouf/ruflow/agent-performance-monitor/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/henryalouf/ruflow/agent-performance-monitor"><img src="https://agentmods.dev/badge/skills/henryalouf/ruflow/agent-performance-monitor.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 | $0.00016 | $0.04172 |
| Opus 5 | $0.00008 | $0.02086 |
| Sonnet 5 | $0.00003 | $0.00834 |
| Haiku 4.5 | $0.00002 | $0.00417 |
Grade A, and why
agent-performance-monitor 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 9d 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 agent-performance-monitor — 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 — 677 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: Performance Monitor type: agent category: optimization description: Real-time metrics collection, bottleneck analysis, SLA monitoring and anomaly detection
Performance Monitor Agent
Agent Profile
- Name: Performance Monitor
- Type: Performance Optimization Agent
- Specialization: Real-time metrics collection and bottleneck analysis
- Performance Focus: SLA monitoring, resource tracking, and anomaly detection
Core Capabilities
1. Real-Time Metrics Collection
// Advanced metrics collection system
class MetricsCollector {
constructor() {
this.collectors = new Map();
this.aggregators = new Map();
this.streams = new Map();
this.alertThresholds = new Map();
}
// Multi-dimensional metrics collection
async collectMetrics() {
const metrics = {
// System metrics
system: await this.collectSystemMetrics(),
// Agent-specific metrics
agents: await this.collectAgentMetrics(),
// Swarm coordination metrics
coordination: await this.collectCoordinationMetrics(),
// Task execution metrics
tasks: await this.collectTaskMetrics(),
// Resource utilization metrics
resources: await this.collectResourceMetrics(),
// Network and communication metrics
network: await this.collectNetworkMetrics()
};
// Real-time processing and analysis
await this.processMetrics(metrics);
return metrics;
}
// System-level metrics
async collectSystemMetrics() {
return {
cpu: {
usage: await this.getCPUUsage(),
loadAverage: await this.getLoadAverage(),
coreUtilization: await this.getCoreUtilization()
},
memory: {
usage: await this.getMemoryUsage(),
available: await this.getAvailableMemory(),
pressure: await this.getMemoryPressure()
},
io: {
diskUsage: await this.getDiskUsage(),
diskIO: await this.getDiskIOStats(),
networkIO: await this.getNetworkIOStats()
},
processes: {
count: await this.getProcessCount(),
threads: await this.getThreadCount(),
handles: await this.getHandleCount()
}
};
}
// Agent performance metrics
async collectAgentMetrics() {
const agents = await mcp.agent_list({});
const agentMetrics = new Map();
for (const agent of agents) {
const metrics = await mcp.agent_metrics({ agentId: agent.id });
agentMetrics.set(agent.id, {
...metrics,
efficiency: this.calculateEfficiency(metrics),
responsiveness: this.calculateResponsiveness(metrics),
reliability: this.calculateReliability(metrics)
});
}
return agentMetrics;
}
}
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.
- 9d ago First seen · 677 lines · 16 tokens per session scan A 048ff1c21dc0
agent-performance-monitor is a skill published in the GitHub repository henryalouf/ruflow (129 stars, last pushed 3mo ago), licensed MIT. It adds 16 tokens to every session and 4,172 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 agent-performance-monitor, differing in 0 lines, and is treated as a copy.
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