feat: Phase 5 & 6 — usability, compliance hardening, analytics
Phase 5 (usability + compliance): - In-app notification bell/badge: migration 016 adds read state + per-user RLS + create_in_app_notification SECURITY DEFINER RPC; /api/notifications; wired into incident creation, CAPA assign/verify, escalation cron - Incident closure: new POST /api/incidents/[id]/close (requires verification status + all CAPAs verified); migration 017 locks closed incidents at DB level (update/delete triggers) with append-only incident_addenda + UI panel - Server-side pagination on HSE/supervisor incident inboxes (.range, 25/page) - Investigation form: alcohol/urine test result + witness statement refs (existing schema columns, now editable) - Type-specific intake fields: migration 018 adds incidents.type_details JSONB; whitelist validation; environmental/asset/security/fire field groups in report form; EN/MS/ZH labels; offline queue support - JKKP 8 annual register CSV export (/api/reports/jkkp8) + dashboard button + January statutory deadline banner - Admin page: user invite (service-role client), role/site/active management, site + zone CRUD with QR report links — replaces Phase 0 stub - Evidence gallery thumbnails via Supabase render transform with fallback Phase 6 (analytics): - 12-month stacked trend chart (leading/lagging/other) + top root causes (lib/dashboard/trends.ts pure helpers) - AI rising-risk zones: /api/dashboard/ai/risk-flags aggregates 90-day zone stats, claude-opus-4-8 forced tool_use, panel on HSE + management dashboards, suggestion audit-logged Also fixes 9 pre-existing missing /ims basePath prefixes in client fetches and download links. 132 tests passing, tsc clean, next build clean. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CPf5Rc8QPx6V8KLEEgfKEQ
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Claude Fable 5
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export const dynamic = 'force-dynamic'
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import { NextResponse } from 'next/server'
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import { createClient } from '@/lib/supabase/server'
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import { createAnthropicClient } from '@/lib/claude/client'
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import { getApiKey } from '@/lib/settings'
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type ZoneAggregate = {
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zone: string
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site: string
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total: number
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near_miss: number
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hazard: number
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injury: number
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avg_severity: number | null
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first_half: number
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second_half: number
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}
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export async function POST() {
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const supabase = await createClient()
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const { data: { user }, error: authError } = await supabase.auth.getUser()
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if (authError || !user) return NextResponse.json({ error: 'Unauthorized' }, { status: 401 })
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const { data: profile } = await supabase.from('users').select('role').eq('id', user.id).single()
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if (!profile || !['hse', 'admin', 'management'].includes(profile.role))
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return NextResponse.json({ error: 'Forbidden' }, { status: 403 })
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const now = new Date()
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const ninetyDaysAgo = new Date(now)
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ninetyDaysAgo.setDate(now.getDate() - 90)
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const midpoint = new Date(now)
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midpoint.setDate(now.getDate() - 45)
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const { data: incidents } = await supabase
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.from('incidents')
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.select('incident_type, severity, reported_at, zones (name), sites (name)')
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.gte('reported_at', ninetyDaysAgo.toISOString())
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const rows = incidents ?? []
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if (rows.length === 0)
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return NextResponse.json({ flags: [], summary: 'No incidents in the last 90 days.' })
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const zoneMap = new Map<string, ZoneAggregate & { severitySum: number; severityCount: number }>()
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for (const r of rows) {
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const zone = (r.zones as unknown as { name: string } | null)?.name ?? 'Unknown zone'
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const site = (r.sites as unknown as { name: string } | null)?.name ?? 'Unknown site'
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const key = `${site}|${zone}`
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let agg = zoneMap.get(key)
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if (!agg) {
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agg = {
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zone, site, total: 0, near_miss: 0, hazard: 0, injury: 0,
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avg_severity: null, first_half: 0, second_half: 0, severitySum: 0, severityCount: 0,
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}
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zoneMap.set(key, agg)
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}
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agg.total++
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if (r.incident_type === 'near_miss') agg.near_miss++
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if (r.incident_type === 'hazard') agg.hazard++
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if (r.incident_type === 'injury') agg.injury++
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if (typeof r.severity === 'number') {
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agg.severitySum += r.severity
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agg.severityCount++
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}
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if (new Date(r.reported_at as string) < midpoint) agg.first_half++
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else agg.second_half++
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}
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const aggregates: ZoneAggregate[] = [...zoneMap.values()].map(a => ({
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zone: a.zone,
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site: a.site,
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total: a.total,
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near_miss: a.near_miss,
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hazard: a.hazard,
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injury: a.injury,
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avg_severity: a.severityCount > 0 ? Math.round((a.severitySum / a.severityCount) * 10) / 10 : null,
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first_half: a.first_half,
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second_half: a.second_half,
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}))
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const anthropicKey = await getApiKey(supabase, 'ANTHROPIC_API_KEY')
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const anthropic = createAnthropicClient(anthropicKey)
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let message: Awaited<ReturnType<typeof anthropic.messages.create>>
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try {
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message = await anthropic.messages.create({
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model: 'claude-opus-4-8',
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thinking: { type: 'adaptive' },
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max_tokens: 2048,
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tools: [{
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name: 'flag_rising_risk',
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description: 'Flag warehouse zones showing rising safety risk from 90-day incident aggregates',
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input_schema: {
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type: 'object' as const,
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properties: {
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flags: {
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type: 'array',
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items: {
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type: 'object',
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properties: {
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zone: { type: 'string' },
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site: { type: 'string' },
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risk_level: { type: 'string', enum: ['low', 'medium', 'high'] },
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rationale: { type: 'string', description: 'One or two sentences citing the numbers' },
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recommended_action: { type: 'string', description: 'One concrete preventive action' },
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},
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required: ['zone', 'site', 'risk_level', 'rationale', 'recommended_action'],
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},
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},
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summary: { type: 'string', description: 'Two-sentence overall risk picture' },
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},
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required: ['flags', 'summary'],
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},
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}],
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tool_choice: { type: 'tool', name: 'flag_rising_risk' },
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messages: [{
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role: 'user',
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content: `You are an HSE risk analyst for a Malaysian 3PL warehouse operator. Below are 90-day incident aggregates per zone. "first_half" is incidents in days 90-46, "second_half" is days 45-0 — a rising second_half means worsening trend. Near-miss and hazard reports are leading indicators; injuries are lagging.
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Flag zones with rising or elevated risk (at most 5 flags; do not flag healthy zones). Base every rationale strictly on the numbers given.
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${JSON.stringify(aggregates, null, 2)}`,
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}],
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})
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} catch {
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return NextResponse.json({ error: 'AI service unavailable' }, { status: 503 })
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}
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const toolBlock = message.content.find(b => b.type === 'tool_use')
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if (!toolBlock || toolBlock.type !== 'tool_use')
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return NextResponse.json({ error: 'AI suggestion failed' }, { status: 500 })
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const input = toolBlock.input as { flags?: unknown; summary?: unknown }
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if (!Array.isArray(input.flags) || typeof input.summary !== 'string')
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return NextResponse.json({ error: 'AI returned unexpected structure' }, { status: 500 })
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const flags = input.flags.filter(
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(f: unknown): f is { zone: string; site: string; risk_level: string; rationale: string; recommended_action: string } =>
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typeof f === 'object' && f !== null &&
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typeof (f as Record<string, unknown>).zone === 'string' &&
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typeof (f as Record<string, unknown>).site === 'string' &&
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['low', 'medium', 'high'].includes((f as Record<string, unknown>).risk_level as string) &&
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typeof (f as Record<string, unknown>).rationale === 'string' &&
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typeof (f as Record<string, unknown>).recommended_action === 'string',
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)
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await supabase.rpc('write_audit_log', {
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p_table_name: 'incidents',
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p_record_id: user.id,
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p_action: 'ai_risk_flags',
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p_new_value: { flags, summary: input.summary, model: 'claude-opus-4-8' } as never,
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})
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return NextResponse.json({ flags, summary: input.summary })
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}
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