diff --git a/src/app/api/agents/[id]/diagnostics/route.ts b/src/app/api/agents/[id]/diagnostics/route.ts
new file mode 100644
index 0000000..567d5fa
--- /dev/null
+++ b/src/app/api/agents/[id]/diagnostics/route.ts
@@ -0,0 +1,285 @@
+import { NextRequest, NextResponse } from 'next/server';
+import { getDatabase } from '@/lib/db';
+import { requireRole } from '@/lib/auth';
+import { logger } from '@/lib/logger';
+
+/**
+ * GET /api/agents/[id]/diagnostics - Agent Self-Diagnostics API
+ *
+ * Provides an agent with its own performance metrics, error analysis,
+ * and trend data so it can self-optimize.
+ *
+ * Query params:
+ *   hours   - Time window in hours (default: 24, max: 720 = 30 days)
+ *   section - Comma-separated sections to include (default: all)
+ *             Options: summary, tasks, errors, activity, trends, tokens
+ *
+ * Response includes:
+ *   summary     - High-level KPIs (throughput, error rate, activity count)
+ *   tasks       - Task completion breakdown by status and priority
+ *   errors      - Error frequency, types, and recent error details
+ *   activity    - Activity breakdown by type with hourly timeline
+ *   trends      - Multi-period comparison for trend detection
+ *   tokens      - Token usage by model with cost estimates
+ */
+export async function GET(
+  request: NextRequest,
+  { params }: { params: Promise<{ id: string }> }
+) {
+  const auth = requireRole(request, 'viewer');
+  if ('error' in auth) return NextResponse.json({ error: auth.error }, { status: auth.status });
+
+  try {
+    const db = getDatabase();
+    const resolvedParams = await params;
+    const agentId = resolvedParams.id;
+    const workspaceId = auth.user.workspace_id ?? 1;
+
+    // Resolve agent by ID or name
+    let agent: any;
+    if (/^\d+$/.test(agentId)) {
+      agent = db.prepare('SELECT id, name, role, status, last_seen, created_at FROM agents WHERE id = ? AND workspace_id = ?').get(Number(agentId), workspaceId);
+    } else {
+      agent = db.prepare('SELECT id, name, role, status, last_seen, created_at FROM agents WHERE name = ? AND workspace_id = ?').get(agentId, workspaceId);
+    }
+
+    if (!agent) {
+      return NextResponse.json({ error: 'Agent not found' }, { status: 404 });
+    }
+
+    const { searchParams } = new URL(request.url);
+    const hours = Math.min(Math.max(parseInt(searchParams.get('hours') || '24', 10) || 24, 1), 720);
+    const sectionParam = searchParams.get('section') || 'summary,tasks,errors,activity,trends,tokens';
+    const sections = new Set(sectionParam.split(',').map(s => s.trim()));
+
+    const now = Math.floor(Date.now() / 1000);
+    const since = now - hours * 3600;
+
+    const result: Record<string, any> = {
+      agent: { id: agent.id, name: agent.name, role: agent.role, status: agent.status },
+      timeframe: { hours, since, until: now },
+    };
+
+    if (sections.has('summary')) {
+      result.summary = buildSummary(db, agent.name, workspaceId, since);
+    }
+
+    if (sections.has('tasks')) {
+      result.tasks = buildTaskMetrics(db, agent.name, workspaceId, since);
+    }
+
+    if (sections.has('errors')) {
+      result.errors = buildErrorAnalysis(db, agent.name, workspaceId, since);
+    }
+
+    if (sections.has('activity')) {
+      result.activity = buildActivityBreakdown(db, agent.name, workspaceId, since);
+    }
+
+    if (sections.has('trends')) {
+      result.trends = buildTrends(db, agent.name, workspaceId, hours);
+    }
+
+    if (sections.has('tokens')) {
+      result.tokens = buildTokenMetrics(db, agent.name, workspaceId, since);
+    }
+
+    return NextResponse.json(result);
+  } catch (error) {
+    logger.error({ err: error }, 'GET /api/agents/[id]/diagnostics error');
+    return NextResponse.json({ error: 'Failed to fetch diagnostics' }, { status: 500 });
+  }
+}
+
+/** High-level KPIs */
+function buildSummary(db: any, agentName: string, workspaceId: number, since: number) {
+  const tasksDone = (db.prepare(
+    `SELECT COUNT(*) as c FROM tasks WHERE assigned_to = ? AND workspace_id = ? AND status = 'done' AND updated_at >= ?`
+  ).get(agentName, workspaceId, since) as any).c;
+
+  const tasksTotal = (db.prepare(
+    `SELECT COUNT(*) as c FROM tasks WHERE assigned_to = ? AND workspace_id = ?`
+  ).get(agentName, workspaceId) as any).c;
+
+  const activityCount = (db.prepare(
+    `SELECT COUNT(*) as c FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ?`
+  ).get(agentName, workspaceId, since) as any).c;
+
+  const errorCount = (db.prepare(
+    `SELECT COUNT(*) as c FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ? AND type LIKE '%error%'`
+  ).get(agentName, workspaceId, since) as any).c;
+
+  const errorRate = activityCount > 0 ? Math.round((errorCount / activityCount) * 10000) / 100 : 0;
+
+  return {
+    tasks_completed: tasksDone,
+    tasks_total: tasksTotal,
+    activity_count: activityCount,
+    error_count: errorCount,
+    error_rate_percent: errorRate,
+  };
+}
+
+/** Task completion breakdown */
+function buildTaskMetrics(db: any, agentName: string, workspaceId: number, since: number) {
+  const byStatus = db.prepare(
+    `SELECT status, COUNT(*) as count FROM tasks WHERE assigned_to = ? AND workspace_id = ? GROUP BY status`
+  ).all(agentName, workspaceId) as Array<{ status: string; count: number }>;
+
+  const byPriority = db.prepare(
+    `SELECT priority, COUNT(*) as count FROM tasks WHERE assigned_to = ? AND workspace_id = ? GROUP BY priority`
+  ).all(agentName, workspaceId) as Array<{ priority: string; count: number }>;
+
+  const recentCompleted = db.prepare(
+    `SELECT id, title, priority, updated_at FROM tasks WHERE assigned_to = ? AND workspace_id = ? AND status = 'done' AND updated_at >= ? ORDER BY updated_at DESC LIMIT 10`
+  ).all(agentName, workspaceId, since) as any[];
+
+  // Estimate throughput: tasks completed per day in the window
+  const windowDays = Math.max((Math.floor(Date.now() / 1000) - since) / 86400, 1);
+  const completedInWindow = recentCompleted.length;
+  const throughputPerDay = Math.round((completedInWindow / windowDays) * 100) / 100;
+
+  return {
+    by_status: Object.fromEntries(byStatus.map(r => [r.status, r.count])),
+    by_priority: Object.fromEntries(byPriority.map(r => [r.priority, r.count])),
+    recent_completed: recentCompleted,
+    throughput_per_day: throughputPerDay,
+  };
+}
+
+/** Error frequency and analysis */
+function buildErrorAnalysis(db: any, agentName: string, workspaceId: number, since: number) {
+  const errorActivities = db.prepare(
+    `SELECT type, COUNT(*) as count FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ? AND (type LIKE '%error%' OR type LIKE '%fail%') GROUP BY type ORDER BY count DESC`
+  ).all(agentName, workspaceId, since) as Array<{ type: string; count: number }>;
+
+  const recentErrors = db.prepare(
+    `SELECT id, type, description, data, created_at FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ? AND (type LIKE '%error%' OR type LIKE '%fail%') ORDER BY created_at DESC LIMIT 20`
+  ).all(agentName, workspaceId, since) as any[];
+
+  return {
+    by_type: errorActivities,
+    total: errorActivities.reduce((sum, e) => sum + e.count, 0),
+    recent: recentErrors.map(e => ({
+      ...e,
+      data: e.data ? JSON.parse(e.data) : null,
+    })),
+  };
+}
+
+/** Activity breakdown with hourly timeline */
+function buildActivityBreakdown(db: any, agentName: string, workspaceId: number, since: number) {
+  const byType = db.prepare(
+    `SELECT type, COUNT(*) as count FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ? GROUP BY type ORDER BY count DESC`
+  ).all(agentName, workspaceId, since) as Array<{ type: string; count: number }>;
+
+  const timeline = db.prepare(
+    `SELECT (created_at / 3600) * 3600 as hour_bucket, COUNT(*) as count FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ? GROUP BY hour_bucket ORDER BY hour_bucket ASC`
+  ).all(agentName, workspaceId, since) as Array<{ hour_bucket: number; count: number }>;
+
+  return {
+    by_type: byType,
+    timeline: timeline.map(t => ({
+      timestamp: t.hour_bucket,
+      hour: new Date(t.hour_bucket * 1000).toISOString(),
+      count: t.count,
+    })),
+  };
+}
+
+/** Multi-period trend comparison for anomaly/trend detection */
+function buildTrends(db: any, agentName: string, workspaceId: number, hours: number) {
+  const now = Math.floor(Date.now() / 1000);
+
+  // Compare current period vs previous period of same length
+  const currentSince = now - hours * 3600;
+  const previousSince = currentSince - hours * 3600;
+
+  const periodMetrics = (since: number, until: number) => {
+    const activities = (db.prepare(
+      `SELECT COUNT(*) as c FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ? AND created_at < ?`
+    ).get(agentName, workspaceId, since, until) as any).c;
+
+    const errors = (db.prepare(
+      `SELECT COUNT(*) as c FROM activities WHERE actor = ? AND workspace_id = ? AND created_at >= ? AND created_at < ? AND (type LIKE '%error%' OR type LIKE '%fail%')`
+    ).get(agentName, workspaceId, since, until) as any).c;
+
+    const tasksCompleted = (db.prepare(
+      `SELECT COUNT(*) as c FROM tasks WHERE assigned_to = ? AND workspace_id = ? AND status = 'done' AND updated_at >= ? AND updated_at < ?`
+    ).get(agentName, workspaceId, since, until) as any).c;
+
+    return { activities, errors, tasks_completed: tasksCompleted };
+  };
+
+  const current = periodMetrics(currentSince, now);
+  const previous = periodMetrics(previousSince, currentSince);
+
+  const pctChange = (cur: number, prev: number) => {
+    if (prev === 0) return cur > 0 ? 100 : 0;
+    return Math.round(((cur - prev) / prev) * 10000) / 100;
+  };
+
+  return {
+    current_period: { since: currentSince, until: now, ...current },
+    previous_period: { since: previousSince, until: currentSince, ...previous },
+    change: {
+      activities_pct: pctChange(current.activities, previous.activities),
+      errors_pct: pctChange(current.errors, previous.errors),
+      tasks_completed_pct: pctChange(current.tasks_completed, previous.tasks_completed),
+    },
+    alerts: buildTrendAlerts(current, previous),
+  };
+}
+
+/** Generate automatic alerts from trend data */
+function buildTrendAlerts(current: { activities: number; errors: number; tasks_completed: number }, previous: { activities: number; errors: number; tasks_completed: number }) {
+  const alerts: Array<{ level: string; message: string }> = [];
+
+  // Error rate spike
+  if (current.errors > 0 && previous.errors > 0) {
+    const errorIncrease = (current.errors - previous.errors) / previous.errors;
+    if (errorIncrease > 0.5) {
+      alerts.push({ level: 'warning', message: `Error count increased ${Math.round(errorIncrease * 100)}% vs previous period` });
+    }
+  } else if (current.errors > 3 && previous.errors === 0) {
+    alerts.push({ level: 'warning', message: `New error pattern: ${current.errors} errors (none in previous period)` });
+  }
+
+  // Throughput drop
+  if (previous.tasks_completed > 0 && current.tasks_completed === 0) {
+    alerts.push({ level: 'info', message: 'No tasks completed in current period (possible stall)' });
+  } else if (previous.tasks_completed > 2 && current.tasks_completed < previous.tasks_completed * 0.5) {
+    alerts.push({ level: 'info', message: `Task throughput dropped ${Math.round((1 - current.tasks_completed / previous.tasks_completed) * 100)}%` });
+  }
+
+  // Activity drop (possible offline)
+  if (previous.activities > 5 && current.activities < previous.activities * 0.25) {
+    alerts.push({ level: 'warning', message: `Activity dropped ${Math.round((1 - current.activities / previous.activities) * 100)}% — agent may be stalled` });
+  }
+
+  return alerts;
+}
+
+/** Token usage by model */
+function buildTokenMetrics(db: any, agentName: string, workspaceId: number, since: number) {
+  try {
+    // session_id on token_usage may store agent name or session key
+    const byModel = db.prepare(
+      `SELECT model, SUM(input_tokens) as input_tokens, SUM(output_tokens) as output_tokens, COUNT(*) as request_count FROM token_usage WHERE session_id = ? AND workspace_id = ? AND created_at >= ? GROUP BY model ORDER BY (input_tokens + output_tokens) DESC`
+    ).all(agentName, workspaceId, since) as Array<{ model: string; input_tokens: number; output_tokens: number; request_count: number }>;
+
+    const total = byModel.reduce((acc, r) => ({
+      input_tokens: acc.input_tokens + r.input_tokens,
+      output_tokens: acc.output_tokens + r.output_tokens,
+      requests: acc.requests + r.request_count,
+    }), { input_tokens: 0, output_tokens: 0, requests: 0 });
+
+    return {
+      by_model: byModel,
+      total,
+    };
+  } catch {
+    // token_usage table may not exist
+    return { by_model: [], total: { input_tokens: 0, output_tokens: 0, requests: 0 } };
+  }
+}