Intelligence

Show the intelligence system dashboard:

1. Call mcp__claude-flow__hooks_intelligence_stats to get pattern counts, trajectory history, and SONA learning state.
2. Call mcp__claude-flow__hooks_metrics to get the metrics dashboard (trajectory throughput, learn-cycle latency, pattern delta).
3. Call mcp__claude-flow__hooks_model-stats for 3-tier model routing distribution (Tier 1 booster / Tier 2 Haiku / Tier 3 Sonnet/Opus).
4. Call mcp__claude-flow__neural_status for neural pattern + SONA / MoE state.
5. (Optional --why <task>) — Call mcp__claude-flow__hooks_explain with the task to get the routing rationale.

Present a summary table:

• Pattern count + active trajectories (from intelligence_stats)
• Tier distribution % (from model-stats)
• Last consolidation timestamp (from neural_status / intelligence_stats)
• Recent metric deltas (from hooks_metrics)
• Routing rationale paragraph (only when --why given)

If patterns are stale, suggest:

mcp tool call hooks_pretrain --json
mcp tool call agentdb_consolidate --json