Add comprehensive documentation for FlowSight project

- Introduced AGENT-SPECS.md detailing the specifications for seven agents including their inputs, processing steps, and outputs.
- Created API-REFERENCE.md outlining the Sectors API v2 endpoints, parameters, costs, and usage.
- Developed API.md to specify backend routes, request/response structures, and error handling.
- Established ARCHITECTURE.md to describe the project layout, conventions, scheduler, and citation pipeline.
- Added DATA-MODEL.md to define the database schema, tables, and seed strategy.
- Compiled PLAN.md to outline the project concept, problem statement, unique features, and implementation timeline.
- Created README.md as an index for documentation with links to all relevant files.
- Documented ROUTINES.md detailing the seven automated routines, their schedules, inputs, detection logic, and delivery formats.
- Introduced TECH-STACK.md to specify the technology choices and rationale for both backend and frontend components.

docs/DATA-MODEL.md

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+# Data model
+
+SQLite for the hackathon; schema kept Postgres-compatible (serial → integer PK,
+JSON → TEXT with JSON1, no SQLite-only DDL). Migrations numbered in
+`backend/app/store/migrations/`.
+
+## Tables
+
+- `snapshots(id, ticker, date, source, payload_json, fetched_at)` — raw API rows.
+  Index (ticker, date, source). Retention: 180d, then compact to weekly.
+- `broker_activity(broker_code, ticker, date, buy, sell, net, lots, freq, avg_price)`
+  Index (ticker, date), (broker_code, date).
+- `foreign_flow(ticker, date, net_inflow)` — PK (ticker, date).
+- `news_items(id, ticker, date, source, sentiment, confidence, url, title)` —
+  Index (ticker, date).
+- `filings(id, ticker, date, holder_type, txn_type, volume, price)` — Index (ticker, date).
+- `routines(id, user_key, type, schedule_cron, channels_json, enabled)` — 7 types (R1–R7).
+- `routine_runs(id, routine_id, started_at, status, payload_json, credits_used)`.
+- `alerts(id, user_key, name, rule_json, channels_json, last_fired)`.
+- `alert_events(id, alert_id, ticker, date, message, context_json, citations_json)`.
+- `watchlists(user_key, ticker, added_at)` — PK (user_key, ticker).
+- `reports(id, ticker, generated_at, payload_json, citations_json)`.
+- `agent_accuracy(id, agent, ticker, prediction, predict_date, resolved, hit, actual_return)`.
+- `briefings(date, payload_json, citations_json)` — PK date.
+- `credit_ledger(date, endpoint, calls, credits)` — daily spend audit.
+
+## Seed strategy
+
+`seed.py` loads one historical trading week into snapshots + derived tables so the
+full demo (briefing → radar → report → interrogation) runs offline. Fixtures live in
+`tests/fixtures/` as JSON exports of real API shapes (field names match schema.json).
+
+## Cursors
+
+- `meta(key, value)`: `quarterly_since` (universe poll cursor), `news_since`,
+  `filings_since` — persisted so restarts resume incrementally.