# Performance Analysis > Performance Analysis - Skill: `dnyoussef/performance-analysis` (Agent Skill, multi-file: 29 files) - Install (CLI): `npx skillmds@latest add dnyoussef/performance-analysis` - Raw SKILL.md: https://api.skillmd.com/api/skills/dnyoussef/performance-analysis/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: DNYoussef (https://skillmd.com/u/dnyoussef) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/dnyoussef/performance-analysis --- /*============================================================================*/ /* SKILL SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: SKILL version: 1.0.0 description: | [assert|neutral] SKILL skill for operations workflows [ground:given] [conf:0.95] [state:confirmed] category: operations tags: - general author: system cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute SKILL workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic operations processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "SKILL", category: "operations", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed] ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. /*----------------------------------------------------------------------------*/ /* S2 TRIGGER CONDITIONS */ /*----------------------------------------------------------------------------*/ [define|neutral] TRIGGER_POSITIVE := { keywords: ["SKILL", "operations", "workflow"], context: "user needs SKILL capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ # Performance Analysis Skill ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. Comprehensive performance analysis suite for identifying bottlenecks, profiling swarm operations, generating detailed reports, and providing actionable optimization recommendations. ## Overview This skill consolidates all performance analysis capabilities: - **Bottleneck Detection**: Identify performance bottlenecks across communication, processing, memory, and network - **Performance Profiling**: Real-time monitoring and historical analysis of swarm operations - **Report Generation**: Create comprehensive performance reports in multiple formats - **Optimization Recommendations**: AI-powered suggestions for improving performance ## Quick Start ### Basic Bottleneck Detection ```bash npx claude-flow bottleneck detect ``` ### Generate Performance Report ```bash npx claude-flow analysis performance-report --format html --include-metrics ``` ### Analyze and Auto-Fix ```bash npx claude-flow bottleneck detect --fix --threshold 15 ``` ## Core Capabilities ### 1. Bottleneck Detection #### Command Syntax ```bash npx claude-flow bottleneck detect [options] ``` #### Options - `--swarm-id, -s ` - Analyze specific swarm (default: current) - `--time-range, -t ` - Analysis period: 1h, 24h, 7d, all (default: 1h) - `--threshold ` - Bottleneck threshold percentage (default: 20) - `--export, -e ` - Export analysis to file - `--fix` - Apply automatic optimizations #### Usage Examples ```bash # Basic detection for current swarm npx claude-flow bottleneck detect # Analyze specific swarm over 24 hours npx claude-flow bottleneck detect --swarm-id swarm-123 -t 24h # Export detailed analysis npx claude-flow bottleneck detect -t 24h -e bottlenecks.json # Auto-fix detected issues npx claude-flow bottleneck detect --fix --threshold 15 # Low threshold for sensitive detection npx claude-flow bottleneck detect --threshold 10 --export critical-issues.json ``` #### Metrics Analyzed **Communication Bottlenecks:** - Message queue delays - Agent response times - Coordination overhead - Memory access patterns - Inter-agent communication latency **Processing Bottlenecks:** - Task completion times - Agent utilization rates - Parallel execution efficiency - Resource contention - CPU/memory usage patterns **Memory Bottlenecks:** - Cache hit rates - Memory access patterns - Storage I/O performance - Neural pattern loading times - Memory allocation efficiency **Network Bottlenecks:** - API call latency - MCP communication delays - External service timeouts - Concurrent request limits - Network throughput issues #### Output Format ``` 🔍 Bottleneck Analysis Report ━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 Summary ├── Time Range: Last 1 hour ├── Agents Analyzed: 6 ├── Tasks Processed: 42 └── Critical Issues: 2 🚨 Critical Bottlenecks 1. Agent Communication (35% impact) └── coordinator → coder-1 messages delayed by 2.3s avg 2. Memory Access (28% impact) └── Neural pattern loading taking 1.8s per access ⚠️ Warning Bottlenecks 1. Task Queue (18% impact) └── 5 tasks waiting > 10s for assignment 💡 Recommendations 1. Switch to hierarchical topology (est. 40% improvement) 2. Enable memory caching (est. 25% improvement) 3. Increase agent concurrency to 8 (est. 20% improvement) ✅ Quick Fixes Available Run with --fix to apply: - Enable smart caching - Optimize message routing - Adjust agent priorities ``` ### 2. Performance Profiling #### Real-time Detection Automatic analysis during task execution: - Execution time vs. complexity - Agent utilization rates - Resource constraints - Operation patterns #### Common Bottleneck Patterns **Time Bottlenecks:** - Tasks taking > 5 minutes - Sequential operations that could parallelize - Redundant file operations - Inefficient algorithm implementations **Coordination Bottlenecks:** - Single agent for complex tasks - Unbalanced agent workloads - Poor topology selection - Excessive s /*----------------------------------------------------------------------------*/ /* S4 SUCCESS CRITERIA */ /*----------------------------------------------------------------------------*/ [define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S5 MCP INTEGRATION */ /*----------------------------------------------------------------------------*/ [define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S6 MEMORY NAMESPACE */ /*----------------------------------------------------------------------------*/ [define|neutral] MEMORY_NAMESPACE := { pattern: "skills/operations/SKILL/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "SKILL-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S7 SKILL COMPLETION VERIFICATION */ /*----------------------------------------------------------------------------*/ [direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S8 ABSOLUTE RULES */ /*----------------------------------------------------------------------------*/ [direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* PROMISE */ /*----------------------------------------------------------------------------*/ [commit|confident] SKILL_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]