d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
59 lines
1.3 KiB
Markdown
59 lines
1.3 KiB
Markdown
# Performance Bottleneck Analysis
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## Purpose
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Identify and resolve performance bottlenecks in your development workflow.
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## Automated Analysis
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### 1. Real-time Detection
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The post-task hook automatically analyzes:
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- Execution time vs. complexity
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- Agent utilization rates
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- Resource constraints
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- Operation patterns
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### 2. Common Bottlenecks
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**Time Bottlenecks:**
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- Tasks taking > 5 minutes
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- Sequential operations that could parallelize
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- Redundant file operations
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**Coordination Bottlenecks:**
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- Single agent for complex tasks
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- Unbalanced agent workloads
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- Poor topology selection
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**Resource Bottlenecks:**
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- High operation count (> 100)
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- Memory constraints
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- I/O limitations
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### 3. Improvement Suggestions
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```
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Tool: mcp__claude-flow__task_results
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Parameters: {"taskId": "task-123", "format": "detailed"}
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Result includes:
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{
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"bottlenecks": [
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{
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"type": "coordination",
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"severity": "high",
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"description": "Single agent used for complex task",
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"recommendation": "Spawn specialized agents for parallel work"
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}
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],
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"improvements": [
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{
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"area": "execution_time",
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"suggestion": "Use parallel task execution",
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"expectedImprovement": "30-50% time reduction"
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}
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]
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}
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```
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## Continuous Optimization
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The system learns from each task to prevent future bottlenecks! |