feat(timeline): add pulse animation for in-flight drag mutations

Allocation bars that have active optimistic overrides (post-drag, awaiting server confirmation) now pulse subtly via animate-pulse. The pending set is derived from the existing optimisticAllocations map keys, requiring no additional state. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-09 13:28:46 +02:00
parent 7a5e98e2e9
commit 1df208dbcc
386 changed files with 657 additions and 81650 deletions
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-# bottleneck detect
-
-Analyze performance bottlenecks in swarm operations and suggest optimizations.
-
-## Usage
-
-```bash
-npx claude-flow bottleneck detect [options]
-```
-
-## Options
-
- `--swarm-id, -s <id>` - Analyze specific swarm (default: current)
- `--time-range, -t <range>` - Analysis period: 1h, 24h, 7d, all (default: 1h)
- `--threshold <percent>` - Bottleneck threshold percentage (default: 20)
- `--export, -e <file>` - Export analysis to file
- `--fix` - Apply automatic optimizations
-
-## Examples
-
-### Basic bottleneck detection
-
-```bash
-npx claude-flow bottleneck detect
-```
-
-### Analyze specific swarm
-
-```bash
-npx claude-flow bottleneck detect --swarm-id swarm-123
-```
-
-### Last 24 hours with export
-
-```bash
-npx claude-flow bottleneck detect -t 24h -e bottlenecks.json
-```
-
-### Auto-fix detected issues
-
-```bash
-npx claude-flow bottleneck detect --fix --threshold 15
-```
-
-## Metrics Analyzed
-
-### Communication Bottlenecks
-
- Message queue delays
- Agent response times
- Coordination overhead
- Memory access patterns
-
-### Processing Bottlenecks
-
- Task completion times
- Agent utilization rates
- Parallel execution efficiency
- Resource contention
-
-### Memory Bottlenecks
-
- Cache hit rates
- Memory access patterns
- Storage I/O performance
- Neural pattern loading
-
-### Network Bottlenecks
-
- API call latency
- MCP communication delays
- External service timeouts
- Concurrent request limits
-
-## 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
-```
-
-## Automatic Fixes
-
-When using `--fix`, the following optimizations may be applied:
-
-1. **Topology Optimization**
-
-   - Switch to more efficient topology
-   - Adjust communication patterns
-   - Reduce coordination overhead
-
-2. **Caching Enhancement**
-
-   - Enable memory caching
-   - Optimize cache strategies
-   - Preload common patterns
-
-3. **Concurrency Tuning**
-
-   - Adjust agent counts
-   - Optimize parallel execution
-   - Balance workload distribution
-
-4. **Priority Adjustment**
-   - Reorder task queues
-   - Prioritize critical paths
-   - Reduce wait times
-
-## Performance Impact
-
-Typical improvements after bottleneck resolution:
-
- **Communication**: 30-50% faster message delivery
- **Processing**: 20-40% reduced task completion time
- **Memory**: 40-60% fewer cache misses
- **Overall**: 25-45% performance improvement
-
-## Integration with Claude Code
-
-```javascript
-// Check for bottlenecks in Claude Code
-mcp__claude-flow__bottleneck_detect {
-  timeRange: "1h",
-  threshold: 20,
-  autoFix: false
-}
-```
-
-## See Also
-
- `performance report` - Detailed performance analysis
- `token usage` - Token optimization analysis
- `swarm monitor` - Real-time monitoring
- `cache manage` - Cache optimization