Output format·Analytics & Monitoring·v1.0.0

Performance Analysis

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms.

You say
Buy it · $29 Read it before you buy $29 Written by ruvnet · unverified publisher
Context cost
3.7k tokensestimated from the bundle, loaded when it triggers
Bundle
1 file · 14.7 kBtext throughout, nothing executable
Licence
MITpaid listing
Last change
v1.0.0
Servers it uses
Noneruns standalone

What it does

Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms

Installed, it changes the agent in these ways.

What this skill changes about the agent is not written down here yet. The listing was collected from its source, and the description is in its own SKILL.md.

Output format

Produces one artefact, exactly shaped.

performancebottleneckoptimizationprofilingmetricsanalysisanalytics

The skill itself

This is the whole product. A skill is instructions the model reads, so there is nothing behind the listing you cannot see first — the front matter loads with every session, and the body below it loads when the skill triggers.

SKILL.md14.7 kB · 564 lines
--- name: performance-analysis version: 1.0.0 description: Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms category: monitoring tags: [performance, bottleneck, optimization, profiling, metrics, analysis] author: Claude Flow Team ---
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
In the file
SKILL.md1,820 words
Files1
LicenceMIT
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈70
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
3,605
on trigger
The instruction body, read only when the skill fires.
1.8%
of a 200k window
Ten skills this size would take about 18% of the window before you open a file.
050k100k150k200k context window

3.7k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Middling. Fine to keep on in a project where you use it weekly, worth unloading in one where you never do.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

Adoption
Installsnone yet
Ratingno reviews yet

The procedure it runs

The procedure has not been published here. It is in the skill’s own SKILL.md, which its author has not sent to the marketplace yet.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

It writes no files and reaches no network. All it changes is how the model reasons and writes.

What it asks for
Writes filesno
Network accessno

Read from the allowed-tools line of this skill’s own SKILL.md. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

1 file, 14.7 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md14.7 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 1 file you can review in full before installing. The MIT licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

$29 once
Performance Analysis · MIT · ruvnet
one-time
Price$29 once
LicenceMIT — the author’s, unchanged by this purchase
Paid throughStripe, once, on the card you add at the checkout
Keeps workingfor good — the files are yours once they are on disk
Updatesevery release of 1.x through this account

You can read the whole bundle before paying — the SKILL.md above is the product, not a preview of it. What the money buys is the delivery: the folder packaged and handed to your machine by key, every update its author ships, and our support if it does not do what this listing says. The terms of use are MIT, set by the author and unchanged by buying it here.

Payment runs through Stripe, on a page like this one rather than a redirect. Once there is an account it joins the same mcprush invoice as everything else you run, so there is never a second card to enter.

Which clients pick it up on their own

A skill is a folder of text. A client with a skills folder reads it without being told; everywhere else the same text works, it is just handed to the model rather than found.

Claude Code.claude/skills/
Claude Desktop
ChatGPT
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok.grok/skills/
Zed.agents/skills/
Windsurf.windsurf/skills/
Agent SDK.claude/skills/
HTTP / API
This release
Version1.0.0
Publishedno release date on file
Price$29
Referenceruvnet/performance-analysis

Versions

v1.0.0 is what is on the shelf; no release here carries a date. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

v1.0.0
  • No earlier releases have been published to the marketplace.
Pinning

Put ruvnet/performance-analysis@1.0.0 in the install command to hold this exact version. Without the suffix you get whatever is current the day you install, and nothing moves under you afterwards.

Reviews

no reviews yet · no installs yet

Nobody has reviewed this skill yet. The rating is the mean of the reviews written here, so there is none until somebody writes the first.

Who can post

Only accounts that have had the skill installed for fourteen days, so a review is written after living with it rather than after reading it. Publishers may reply once.

Publisher
Servers0