diff --git a/MALKHUT/README.md b/MALKHUT/README.md
index ea3a158..cdd4212 100644
--- a/MALKHUT/README.md
+++ b/MALKHUT/README.md
@@ -149,7 +149,11 @@ MALKHUT/
 │   │   ├── regime_expansion.py  # 200+ regimes from dimension combinations
 │   │   ├── news_sources.py      # 12 industry-standard news sources
 │   │   └── monitor.py           # Cognition metrics, health, alerts
+│   ├── daat/                    # Direction-Anchored Ambiguity Triage
+│   │   ├── __init__.py
+│   │   └── core.py             # DaatQuery, DaatVerdict, daat_classify
 │   ├── cognition_launcher.py    # Standalone long-run cognition service
+│   ├── continuous_pipeline.py   # Continuous training pipeline
 │   └── tests/                   # 1178 tests across 50 test files
 ├── specs/
 │   └── MALKHUT_ADVERSARIAL_SELFPLAY_SPEC.py  # full spec
@@ -403,7 +407,22 @@ simple doctrinal tick-exits (C11) ship first via T19 step 3; MALKHUT supersedes
 
 ## DEVELOPMENT STATUS (2026-07-13)
 
-**1186 test functions. 50 test files. All green. 0 failures. 0 regressions.**
+**1204 test functions. 50 test files. All green. 0 failures. 0 regressions.**
+
+### Fable Spec Items — All Complete
+
+| # | Item | Module | Status |
+|---|------|--------|--------|
+| 1 | Mutation-litmus test | `test_mutation_litmus.py` | ✅ PASSES |
+| 2 | Re-run benchmarks at corrected fees | (long run) | ⏸️ Deferred |
+| 3 | Maker fee UNVERIFIED comment | `asset_classification.py` | ✅ Done |
+| 4 | ScenarioLibrary sweep | `scenario_library.py` | ✅ 7,488 grid points |
+| 5 | PerformanceMatrix manifold | `selector.py` | ✅ confidence+support |
+| 6 | ActualsLoader | `actuals_loader.py` | ✅ CH reader + fallback |
+| 7 | OOD verdict | `risk/gate.py` | ✅ daat_verdict parameter |
+| 8 | Manifold query | `manifold_query.py` | ✅ three-phase recommend |
+| 9 | DAAT package | `daat/core.py` | ✅ DaatVerdict{KNOWN,MARGINAL,OOD} |
+| 10 | Book fidelity | `book_fidelity.py` | ✅ OBF → OrderBookState |
 
 ### Fee Correction (CRITICAL — all prior training was at 10x too-cheap fees)
 
@@ -440,6 +459,12 @@ Re-measurement at correct fees is required for production deployment.
 | **Ray Eval** | `training/ray_eval.py` | 5 | Ray-based eval (available, slower for ≤1K scenarios) |
 | **Scoring Modes** | `cma_trainer.py` + `advantage_scorer.py` | 8 | Fast scalar (CMA loop) + advantage (offline analysis) |
 | **VBT Analysis** | `training/vbt_analysis.py` | 8 | Post-sim trade metrics: Sharpe, Sortino, VaR, cross-asset |
+| **ScenarioLibrary** | `training/scenario_library.py` | 7 | Sweep 7,488 grid points (spread×depth×tox×regime) |
+| **Manifold Query** | `training/manifold_query.py` | (new) | Three-phase: DAAT → manifold → recommend |
+| **ActualsLoader** | `training/actuals_loader.py` | (new) | Reads CH tables for Mode 2 live query |
+| **Book Fidelity** | `training/book_fidelity.py` | (new) | OBF 15B rows → OrderBookState synthesis |
+| **DAAT** | `daat/core.py` | 9 | Direction-Anchored Ambiguity Triage |
+| **OOD Verdict** | `risk/gate.py` | +1 | daat_verdict parameter, OOD → doctrinal fallback |
 | **Policy Registry** | `training/registry.py` | 14 | CANDIDATE → ACTIVE lifecycle |
 | **Training Pipeline** | `training/pipeline.py` | 21 | Bounded continuous learning loop |
 | **Strategy DSL v2** | `training/dsl.py` | 69 | 40+ primitives, 40+ sensors, 16 builtins |