feat: Specialist Desks v2 — COT, Forward Curves, Surprise Index, Hawk/Dove scorer

- COT Positioning: CFTC disaggregated + financial futures (19 markets) via Socrata free API
  net MM position % OI + weekly change stored in cot_data table
- Forward Curves: yfinance front-month vs +3M slope (8 commodities)
  contango/backwardation/flat stored in forward_curve_data table
- Surprise Index: consensus_estimate + actual_value on specialist_reports
  auto-computes surprise_score = actual - consensus on save
- Hawk/Dove Text Scorer: GPT-4o-mini endpoint for CB statements
  score -1..+1, label, summary, key_phrases (forex/bonds: hawk/dove; commodities: bull/bear)
- AI context injection: COT net positioning, forward curve structure,
  surprise scores, upcoming consensus estimates injected into all desk blocks
- Frontend: COT panel (net% bars), Forward Curves panel, SurpriseInput
  on report cards, Hawk/Dove scorer in forex/bonds config tab
- auto_cycle.py: non-blocking COT + curve refresh before each cycle

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

frontend/src/hooks/useApi.ts

@@ -1252,3 +1252,107 @@ export const useUnlinkReportDesk = () => {
     },
   })
 }
+
+// ── COT / Forward Curves / Surprise Index / Hawk-Dove — new types ─────────────
+
+export interface CotEntry {
+  id: number
+  market_name: string
+  commodity: string
+  asset_class: string
+  report_date: string
+  mm_long: number
+  mm_short: number
+  open_interest: number
+  net_position: number
+  net_pct_oi: number
+  change_net: number
+  fetched_at: string
+}
+
+export interface ForwardCurveEntry {
+  id: number
+  asset: string
+  asset_class: string
+  front_price: number | null
+  far_price: number | null
+  slope_pct: number | null
+  structure: 'contango' | 'backwardation' | 'flat' | 'unknown'
+  months_spread: number
+  fetched_at: string
+}
+
+export interface TextSentimentResult {
+  score: number
+  label: string
+  summary: string
+  key_phrases: string[]
+  confidence: 'high' | 'medium' | 'low'
+}
+
+export interface ReportResultUpdate {
+  actual_value?: number | null
+  consensus_estimate?: number | null
+  text_sentiment_score?: number | null
+  text_sentiment_label?: string | null
+  text_sentiment_summary?: string | null
+}
+
+// ── COT Data ──────────────────────────────────────────────────────────────────
+
+export function useCotData() {
+  return useQuery<CotEntry[]>({
+    queryKey: ['specialist-desks', 'cot'],
+    queryFn: () => api.get('/specialist-desks/cot').then(r => r.data),
+    staleTime: 1000 * 60 * 60, // 1h
+  })
+}
+
+export function useFetchCot() {
+  const qc = useQueryClient()
+  return useMutation({
+    mutationFn: () => api.post('/specialist-desks/cot/fetch').then(r => r.data),
+    onSuccess: () => qc.invalidateQueries({ queryKey: ['specialist-desks', 'cot'] }),
+  })
+}
+
+// ── Forward Curves ────────────────────────────────────────────────────────────
+
+export function useForwardCurves() {
+  return useQuery<ForwardCurveEntry[]>({
+    queryKey: ['specialist-desks', 'forward-curves'],
+    queryFn: () => api.get('/specialist-desks/forward-curves').then(r => r.data),
+    staleTime: 1000 * 60 * 60,
+  })
+}
+
+export function useFetchForwardCurves() {
+  const qc = useQueryClient()
+  return useMutation({
+    mutationFn: () => api.post('/specialist-desks/forward-curves/fetch').then(r => r.data),
+    onSuccess: () => qc.invalidateQueries({ queryKey: ['specialist-desks', 'forward-curves'] }),
+  })
+}
+
+// ── Surprise Index ────────────────────────────────────────────────────────────
+
+export function useUpdateReportResult() {
+  const qc = useQueryClient()
+  return useMutation({
+    mutationFn: ({ id, body }: { id: string; body: ReportResultUpdate }) =>
+      api.put(`/specialist-desks/reports/${id}/result`, body).then(r => r.data),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: ['specialist-reports'] })
+      qc.invalidateQueries({ queryKey: ['desk-configs'] })
+    },
+  })
+}
+
+// ── Hawk/Dove Text Scorer ─────────────────────────────────────────────────────
+
+export function useScoreText() {
+  return useMutation({
+    mutationFn: (body: { text: string; report_name: string; desk: string }) =>
+      api.post('/specialist-desks/score-text', body).then(r => r.data) as Promise<TextSentimentResult>,
+  })
+}