Agent Performance MonitorCAUTION
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Overview
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
6f6a05ecd222OBSERVED · 2026-09-27What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: agent-performance-monitor
description: Agent skill for performance-monitor - invoke with $agent-performance-monitor
---
---
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
```javascript
// 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;
}
}
```
### 2. Bottleneck Detection & Analysis
```javascript
// Intelligent bottleneck detection
class BottleneckAnalyzer {
constructor() {
this.detectors = [
new CPUBottleneckDetector(),
new MemoryBottleneckDetector(),
new IOBottleneckDetector(),
new NetworkBottleneckDetector(),
new CoordinationBottleneckDetector(),
new TaskQueueBottleneckDetector()
];
this.patterns = new Map();
this.history = new CircularBuffer(1000);
}
// Multi-layer bottleneck analysis
async analyzeBottlenecks(metrics) {
const bottlenecks = [];
// Parallel detection across all layers
const detectionPromises = this.detectors.map(detector =>
detector.detect(metrics)
);
const results = await Promise.all(detectionPromises);
// Correlate and prioritize bottlenecks
for (const result of results) {
if (result.detected) {
bottlenecks.push({
type: result.type,
severity: result.severity,
component: result.component,
rootCause: result.rootCause,
impact: result.impact,
recommendations: result.recommendations,
timestamp: Date.now()
});
}
}
// Pattern recognition for recurring bottlenecks
await this.updatePatterns(bottlenecks);
return this.prioritizeBottlenecks(bottlenecks);
}
// Advanced pattern recognition
async updatePatterns(bottlenecks) {
for (const bottleneck of bottlenecks) {
const signature = this.createBottleneckSignature(bottleneck);
if (this.patterns.has(signature)) {
const pattern = this.patterns.get(signature);
pattern.frequency++;
pattern.lastOccurrence = Date.now();
pattern.averageInterval = this.calculateAverageInterval(pattern);
} else {
this.patterns.set(signature, {
signature,
frequency: 1,
firstOccurrence: Date.now(),
lastOccurrence: Date.now(),
averageInterval: 0,
predictedNext: null
});
}
}
}
}
```
### 3. SLA Monitoring & Alerting
```javascript
// Service Level Agreement monitoring
class SLAMonitor {
constructor() {
this.slaDefinitions = new Map();
this.violations = new Map();
this.alertChannels = new Set();
this.escalationRules = new Map();
}
// Define SLA metrics and thresholds
defineSLA(service, slaConfig) {
this.slaDefinitions.set(service, {
availability: slaConfig.availability || 99.9, // percentage
responseTime: slaConfig.responseTime || 1000, // milliseconds
throughput: slaConfig.throughput || 100, // requests per second
errorRate: slaConfig.errorRate || 0.1, // percentage
recoveryTime: slaConfig.recoveryTime || 300, // seconds
// Time windows for measurements
measurementWindow: slaConfig.measurementWindow || 300, // seconds
evaluationInterval: slaConfig.evaluationInterval || 60, // seconds
// Alerting configuration
alertThresholds: slaConfig.alerTrust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (4)
crates
plugin/agents
plugin/commands
plugin/skills
Gates applied: no_behavioural_pass.
6f6a05ecd222full audit observations/trust-audit/skill/ruvnet__agent-performance-monitor.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-09-27 | 6f6a05ecd222 | CAUTION | B | 89 | first audit |
Questions
What does the Agent Performance Monitor skill do?
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Is Agent Performance Monitor safe to install?
With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can Agent Performance Monitor access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (6f6a05ecd222), read on 2026-09-27. The repository is watched, and a new audit runs when it changes — this is the first audit.