Add CFTC COT data integration with foundation data model layer

- New extraction package (cftc_cot): downloads yearly Disaggregated Futures ZIPs
  from CFTC, etag-based dedup, dynamic inner filename discovery, gzip normalization
- SQLMesh 3-layer architecture: raw (technical) → foundation (business model) → serving (mart)
- dim_commodity seed: conformed dimension mapping USDA ↔ CFTC codes — the commodity ontology
- fct_cot_positioning: typed, deduplicated weekly positioning facts for all commodities
- obt_cot_positioning: Coffee C mart with COT Index (26w/52w), WoW delta, OI ratios
- Analytics functions + REST API endpoints: /commodities/<code>/positioning[/latest]
- Dashboard widget: Managed Money net, COT Index card, dual-axis Chart.js chart
- 23 passing tests (10 unit + 2 SQLMesh model + existing regression suite)

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

transform/sqlmesh_materia/macros/__init__.py

@@ -8,3 +8,10 @@ def psd_glob(evaluator) -> str:
     """Return a quoted glob path for all PSD CSV gzip files under LANDING_DIR."""
     landing_dir = evaluator.var("LANDING_DIR") or os.environ.get("LANDING_DIR", "data/landing")
     return f"'{landing_dir}/psd/**/*.csv.gzip'"
+
+
+@macro()
+def cot_glob(evaluator) -> str:
+    """Return a quoted glob path for all COT CSV gzip files under LANDING_DIR."""
+    landing_dir = evaluator.var("LANDING_DIR") or os.environ.get("LANDING_DIR", "data/landing")
+    return f"'{landing_dir}/cot/**/*.csv.gzip'"