10# Performance Analysis Skill
11
12Comprehensive performance analysis suite for identifying bottlenecks, profiling swarm operations, generating detailed reports, and providing actionable optimization recommendations.
13
14## Overview
15
16This skill consolidates all performance analysis capabilities:
17- **Bottleneck Detection**: Identify performance bottlenecks across communication, processing, memory, and network
18- **Performance Profiling**: Real-time monitoring and historical analysis of swarm operations
19- **Report Generation**: Create comprehensive performance reports in multiple formats
20- **Optimization Recommendations**: AI-powered suggestions for improving performance
21
22## Quick Start
23
24### Basic Bottleneck Detection
25```bash
26npx claude-flow bottleneck detect
27```
28
29### Generate Performance Report
30```bash
31npx claude-flow analysis performance-report --format html --include-metrics
32```
33
34### Analyze and Auto-Fix
35```bash
36npx claude-flow bottleneck detect --fix --threshold 15
37```
38
39## Core Capabilities
40
41### 1. Bottleneck Detection
42
43#### Command Syntax
44```bash
45npx claude-flow bottleneck detect [options]
46```
47
48#### Options
49- --swarm-id, -s <id> - Analyze specific swarm (default: current)
50- --time-range, -t <range> - Analysis period: 1h, 24h, 7d, all (default: 1h)
51- --threshold <percent> - Bottleneck threshold percentage (default: 20)
52- --export, -e <file> - Export analysis to file
53- --fix - Apply automatic optimizations
54
55#### Usage Examples
56```bash
57# Basic detection for current swarm
58npx claude-flow bottleneck detect
59
60# Analyze specific swarm over 24 hours
61npx claude-flow bottleneck detect --swarm-id swarm-123 -t 24h
62
63# Export detailed analysis
64npx claude-flow bottleneck detect -t 24h -e bottlenecks.json
65
66# Auto-fix detected issues
67npx claude-flow bottleneck detect --fix --threshold 15
68
69# Low threshold for sensitive detection
70npx claude-flow bottleneck detect --threshold 10 --export critical-issues.json
71```
72
73#### Metrics Analyzed
74
75**Communication Bottlenecks:**
76- Message queue delays
77- Agent response times
78- Coordination overhead
79- Memory access patterns
80- Inter-agent communication latency
81
82**Processing Bottlenecks:**
83- Task completion times
84- Agent utilization rates
85- Parallel execution efficiency
86- Resource contention
87- CPU/memory usage patterns
88
89**Memory Bottlenecks:**
90- Cache hit rates
91- Memory access patterns
92- Storage I/O performance
93- Neural pattern loading times
94- Memory allocation efficiency
95
96**Network Bottlenecks:**
97- API call latency
98- MCP communication delays
99- External service timeouts
100- Concurrent request limits
101- Network throughput issues
102
103#### Output Format
104```
105🔍 Bottleneck Analysis Report
106━━━━━━━━━━━━━━━━━━━━━━━━━━━
107
108📊 Summary
109├── Time Range: Last 1 hour
110├── Agents Analyzed: 6
111├── Tasks Processed: 42
112└── Critical Issues: 2
113
114🚨 Critical Bottlenecks
1151. Agent Communication (35% impact)
116 └── coordinator → coder-1 messages delayed by 2.3s avg
117
1182. Memory Access (28% impact)
119 └── Neural pattern loading taking 1.8s per access
120
121⚠️ Warning Bottlenecks
1221. Task Queue (18% impact)
123 └── 5 tasks waiting > 10s for assignment
124
125💡 Recommendations
1261. Switch to hierarchical topology (est. 40% improvement)
1272. Enable memory caching (est. 25% improvement)
1283. Increase agent concurrency to 8 (est. 20% improvement)
129
130✅ Quick Fixes Available
131Run with --fix to apply:
132- Enable smart caching
133- Optimize message routing
134- Adjust agent priorities
135```
136
137### 2. Performance Profiling
138
139#### Real-time Detection
140Automatic analysis during task execution:
141- Execution time vs. complexity
142- Agent utilization rates
143- Resource constraints
144- Operation patterns
145
146#### Common Bottleneck Patterns
147
148**Time Bottlenecks:**
149- Tasks taking > 5 minutes
150- Sequential operations that could parallelize
151- Redundant file operations
152- Inefficient algorithm implementations
153
154**Coordination Bottlenecks:**
155- Single agent for complex tasks
156- Unbalanced agent workloads
157- Poor topology selection
158- Excessive synchronization points
159
160**Resource Bottlenecks:**
161- High operation count (> 100)
162- Memory constraints
163- I/O limitations
164- Thread pool saturation
165
166#### MCP Integration
167```javascript
168// Check for bottlenecks in Claude Code
169mcp__claude-flow__bottleneck_detect({
170 timeRange: "1h",
171 threshold: 20,
172 autoFix: false
173})
174
175// Get detailed task results with bottleneck analysis
176mcp__claude-flow__task_results({
177 taskId: "task-123",
178 format: "detailed"
179})
180```
181
182**Result Format:**
183```json
184{
185 "bottlenecks": [
186 {
187 "type": "coordination",
188 "severity": "high",
189 "description": "Single agent used for complex task",
190 "recommendation": "Spawn specialized agents for parallel work",
191 "impact": "35%",
192 "affectedComponents": ["coordinator", "coder-1"]
193 }
194 ],
195 "improvements": [
196 {
197 "area": "execution_time",
198 "suggestion": "Use parallel task execution",
199 "expectedImprovement": "30-50% time reduction",
200 "implementationSteps": [
201 "Split task into smaller units",
202 "Spawn 3-4 specialized agents",
203 "Use mesh topology for coordination"
204 ]
205 }
206 ],
207 "metrics": {
208 "avgExecutionTime": "142s",
209 "agentUtilization": "67%",
210 "cacheHitRate": "82%",
211 "parallelizationFactor": 1.2
212 }
213}
214```
215
216### 3. Report Generation
217
218#### Command Syntax
219```bash
220npx claude-flow analysis performance-report [options]
221```
222
223#### Options
224- --format <type> - Report format: json, html, markdown (default: markdown)
225- --include-metrics - Include detailed metrics and charts
226- --compare <id> - Compare with previous swarm
227- --time-range <range> - Analysis period: 1h, 24h, 7d, 30d, all
228- --output <file> - Output file path
229- --sections <list> - Comma-separated sections to include
230
231#### Report Sections
2321. **Executive Summary**
233 - Overall performance score
234 - Key metrics overview
235 - Critical findings
236
2372. **Swarm Overview**
238 - Topology configuration
239 - Agent distribution
240 - Task statistics
241
2423. **Performance Metrics**
243 - Execution times
244 - Throughput analysis
245 - Resource utilization
246 - Latency breakdown
247
2484. **Bottleneck Analysis**
249 - Identified bottlenecks
250 - Impact assessment
251 - Optimization priorities
252
2535. **Comparative Analysis** (when --compare used)
254 - Performance trends
255 - Improvement metrics
256 - Regression detection
257
2586. **Recommendations**
259 - Prioritized action items
260 - Expected improvements
261 - Implementation guidance
262
263#### Usage Examples
264```bash
265# Generate HTML report with all metrics
266npx claude-flow analysis performance-report --format html --include-metrics
267
268# Compare current swarm with previous
269npx claude-flow analysis performance-report --compare swarm-123 --format markdown
270
271# Custom output with specific sections
272npx claude-flow analysis performance-report \
273 --sections summary,metrics,recommendations \
274 --output reports/perf-analysis.html \
275 --format html
276
277# Weekly performance report
278npx claude-flow analysis performance-report \
279 --time-range 7d \
280 --include-metrics \
281 --format markdown \
282 --output docs/weekly-performance.md
283
284# JSON format for CI/CD integration
285npx claude-flow analysis performance-report \
286 --format json \
287 --output build/performance.json
288```
289
290#### Sample Markdown Report
291```markdown
292# Performance Analysis Report
293
294## Executive Summary
295- **Overall Score**: 87/100
296- **Analysis Period**: Last 24 hours
297- **Swarms Analyzed**: 3
298- **Critical Issues**: 1
299
300## Key Metrics
301| Metric | Value | Trend | Target |
302|--------|-------|-------|--------|
303| Avg Task Time | 42s | ↓ 12% | 35s |
304| Agent Utilization | 78% | ↑ 5% | 85% |
305| Cache Hit Rate | 91% | → | 90% |
306| Parallel Efficiency | 2.3x | ↑ 0.4x | 2.5x |
307
308## Bottleneck Analysis
309### Critical
3101. **Agent Communication Delay** (Impact: 35%)
311 - Coordinator → Coder messages delayed by 2.3s avg
312 - **Fix**: Switch to hierarchical topology
313
314### Warnings
3151. **Memory Access Pattern** (Impact: 18%)
316 - Neural pattern loading: 1.8s per access
317 - **Fix**: Enable memory caching
318
319## Recommendations
3201. **High Priority**: Switch to hierarchical topology (40% improvement)
3212. **Medium Priority**: Enable memory caching (25% improvement)
3223. **Low Priority**: Increase agent concurrency to 8 (20% improvement)
323```
324
325### 4. Optimization Recommendations
326
327#### Automatic Fixes
328When using --fix, the following optimizations may be applied:
329
330**1. Topology Optimization**
331- Switch to more efficient topology (mesh → hierarchical)
332- Adjust communication patterns
333- Reduce coordination overhead
334- Optimize message routing
335
336**2. Caching Enhancement**
337- Enable memory caching
338- Optimize cache strategies
339- Preload common patterns
340- Implement cache warming
341
342**3. Concurrency Tuning**
343- Adjust agent counts
344- Optimize parallel execution
345- Balance workload distribution
346- Implement load balancing
347
348**4. Priority Adjustment**
349- Reorder task queues
350- Prioritize critical paths
351- Reduce wait times
352- Implement fair scheduling
353
354**5. Resource Optimization**
355- Optimize memory usage
356- Reduce I/O operations
357- Batch API calls
358- Implement connection pooling
359
360#### Performance Impact
361Typical improvements after bottleneck resolution:
362
363- **Communication**: 30-50% faster message delivery
364- **Processing**: 20-40% reduced task completion time
365- **Memory**: 40-60% fewer cache misses
366- **Network**: 25-45% reduced API latency
367- **Overall**: 25-45% total performance improvement
368
369## Advanced Usage
370
371### Continuous Monitoring
372```bash
373# Monitor performance in real-time
374npx claude-flow swarm monitor --interval 5
375
376# Generate hourly reports
377while true; do
378 npx claude-flow analysis performance-report \
379 --format json \
380 --output logs/perf-$(date +%Y%m%d-%H%M).json
381 sleep 3600
382done
383```
384
385### CI/CD Integration
386```yaml
387# .github/workflows/performance.yml
388name: Performance Analysis
389on: [push, pull_request]
390
391jobs:
392 analyze:
393 runs-on: ubuntu-latest
394 steps:
395 - uses: actions/checkout@v2
396 - name: Run Performance Analysis
397 run: |
398 npx claude-flow analysis performance-report \
399 --format json \
400 --output performance.json
401 - name: Check Performance Thresholds
402 run: |
403 npx claude-flow bottleneck detect \
404 --threshold 15 \
405 --export bottlenecks.json
406 - name: Upload Reports
407 uses: actions/upload-artifact@v2
408 with:
409 name: performance-reports
410 path: |
411 performance.json
412 bottlenecks.json
413```
414
415### Custom Analysis Scripts
416```javascript
417// scripts/analyze-performance.js
418const { exec } = require('child_process');
419const fs = require('fs');
420
421async function analyzePerformance() {
422 // Run bottleneck detection
423 const bottlenecks = await runCommand(
424 'npx claude-flow bottleneck detect --format json'
425 );
426
427 // Generate performance report
428 const report = await runCommand(
429 'npx claude-flow analysis performance-report --format json'
430 );
431
432 // Analyze results
433 const analysis = {
434 bottlenecks: JSON.parse(bottlenecks),
435 performance: JSON.parse(report),
436 timestamp: new Date().toISOString()
437 };
438
439 // Save combined analysis
440 fs.writeFileSync(
441 'analysis/combined-report.json',
442 JSON.stringify(analysis, null, 2)
443 );
444
445 // Generate alerts if needed
446 if (analysis.bottlenecks.critical.length > 0) {
447 console.error('CRITICAL: Performance bottlenecks detected!');
448 process.exit(1);
449 }
450}
451
452function runCommand(cmd) {
453 return new Promise((resolve, reject) => {
454 exec(cmd, (error, stdout, stderr) => {
455 if (error) reject(error);
456 else resolve(stdout);
457 });
458 });
459}
460
461analyzePerformance().catch(console.error);
462```
463
464## Best Practices
465
466### 1. Regular Analysis
467- Run bottleneck detection after major changes
468- Generate weekly performance reports
469- Monitor trends over time
470- Set up automated alerts
471
472### 2. Threshold Tuning
473- Start with default threshold (20%)
474- Lower for production systems (10-15%)
475- Higher for development (25-30%)
476- Adjust based on requirements
477
478### 3. Fix Strategy
479- Always review before applying --fix
480- Test fixes in development first
481- Apply fixes incrementally
482- Monitor impact after changes
483
484### 4. Report Integration
485- Include in documentation
486- Share with team regularly
487- Track improvements over time
488- Use for capacity planning
489
490### 5. Continuous Optimization
491- Learn from each analysis
492- Build performance budgets
493- Establish baselines
494- Set improvement goals
495
496## Troubleshooting
497
498### Common Issues
499
500**High Memory Usage**
501```bash
502# Analyze memory bottlenecks
503npx claude-flow bottleneck detect --threshold 10
504
505# Check cache performance
506npx claude-flow cache manage --action stats
507
508# Review memory metrics
509npx claude-flow memory usage
510```
511
512**Slow Task Execution**
513```bash
514# Identify slow tasks
515npx claude-flow task status --detailed
516
517# Analyze coordination overhead
518npx claude-flow bottleneck detect --time-range 1h
519
520# Check agent utilization
521npx claude-flow agent metrics
522```
523
524**Poor Cache Performance**
525```bash
526# Analyze cache hit rates
527npx claude-flow analysis performance-report --sections metrics
528
529# Review cache strategy
530npx claude-flow cache manage --action analyze
531
532# Enable cache warming
533npx claude-flow bottleneck detect --fix
534```
535
536## Integration with Other Skills
537
538- **swarm-orchestration**: Use performance data to optimize topology
539- **memory-management**: Improve cache strategies based on analysis
540- **task-coordination**: Adjust scheduling based on bottlenecks
541- **neural-training**: Train patterns from performance data
542
543## Related Commands
544
545- npx claude-flow swarm monitor - Real-time monitoring
546- npx claude-flow token usage - Token optimization analysis
547- npx claude-flow cache manage - Cache optimization
548- npx claude-flow agent metrics - Agent performance metrics
549- npx claude-flow task status - Task execution analysis
550
551## See Also
552
553- [Bottleneck Detection Guide](/workspaces/claude-code-flow/.claude/commands/analysis/bottleneck-detect.md)
554- [Performance Report Guide](/workspaces/claude-code-flow/.claude/commands/analysis/performance-report.md)
555- [Performance Bottlenecks Overview](/workspaces/claude-code-flow/.claude/commands/analysis/performance-bottlenecks.md)
556- [Swarm Monitoring Documentation](../swarm-orchestration/SKILL.md)
557- [Memory Management Documentation](../memory-management/SKILL.md)
558
559---
560
561**Version**: 1.0.0
562**Last Updated**: 2025-10-19
563**Maintainer**: Claude Flow Team
564