HartmutandClaude Sonnet 4.6
f80808482d
Restores the entire .claude/ infrastructure that was accidentally deleted
in commit 1df208d ('feat(timeline): add pulse animation for in-flight drag
mutations'). Recovered via git checkout 1df208d^.
Restored:
- .claude/commands/ (gitlooper, sparc/, github/, automation/, monitoring/,
optimization/, hooks/, plan, implement, research, review, perf, visualaudit)
- .claude/agents/ (core/, github/, sparc/, v3/, swarm/, templates/, ...)
- .claude/helpers/ (41 scripts incl. hook-handler.cjs, statusline.cjs)
- .claude/skills/ (20 skills incl. sparc-methodology, github-*, v3-*)
- .claude/settings.json (hooks configuration)
Also updated all CapaKraken → Nexus references in affected command files.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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1.3 KiB
Performance Bottleneck Analysis
Purpose
Identify and resolve performance bottlenecks in your development workflow.
Automated Analysis
1. Real-time Detection
The post-task hook automatically analyzes:
- Execution time vs. complexity
- Agent utilization rates
- Resource constraints
- Operation patterns
2. Common Bottlenecks
Time Bottlenecks:
- Tasks taking > 5 minutes
- Sequential operations that could parallelize
- Redundant file operations
Coordination Bottlenecks:
- Single agent for complex tasks
- Unbalanced agent workloads
- Poor topology selection
Resource Bottlenecks:
- High operation count (> 100)
- Memory constraints
- I/O limitations
3. Improvement Suggestions
Tool: mcp__claude-flow__task_results
Parameters: {"taskId": "task-123", "format": "detailed"}
Result includes:
{
"bottlenecks": [
{
"type": "coordination",
"severity": "high",
"description": "Single agent used for complex task",
"recommendation": "Spawn specialized agents for parallel work"
}
],
"improvements": [
{
"area": "execution_time",
"suggestion": "Use parallel task execution",
"expectedImprovement": "30-50% time reduction"
}
]
}
Continuous Optimization
The system learns from each task to prevent future bottlenecks!