quantum-osiris · Nov 10, 2026 · Nov 10, 2026
diff --git a/benchmarks/bench_ledger_append.py b/benchmarks/bench_ledger_append.py
@@ -0,0 +1,119 @@
+#!/usr/bin/env python3
+"""
+bench_ledger_append.py
+Append latency, verify time and tamper detection for the operational journal
+(osiris_cli/journal.py: hash = SHA-256(prev || canonical(entry)), file-locked appends).
+
+Everything runs on a temporary journal; the tracked journal is never touched.
+
+Tamper cases, each applied to a fresh copy of the benchmark journal:
+  edit_field      change one payload field in the middle entry
+  edit_hash       replace the middle entry's stored hash
+  delete_middle   remove the middle entry
+  swap_adjacent   exchange two neighboring entries
+  truncate_tail   remove the last 10 entries
+
+A hash chain alone cannot detect truncate_tail: what remains is a valid chain. Detecting it needs the
+tip (last hash and count) recorded somewhere the attacker cannot rewrite, e.g. signed by an operator
+token. The benchmark reports that case as it is rather than hiding it.
+
+Usage:
+  python benchmarks/bench_ledger_append.py [--n 2000] [--out benchmarks/results_ledger_append.json]
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import platform
+import statistics
+import sys
+import tempfile
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
+
+from osiris_cli.journal import OperationalMerkleLedger  # noqa: E402
+
+
+def _pct(sorted_ms, q):
+    return sorted_ms[min(len(sorted_ms) - 1, int(q * len(sorted_ms)))]
+
+
+def _tamper(lines, case):
+    out = list(lines)
+    mid = len(out) // 2
+    if case == "edit_field":
+        e = json.loads(out[mid])
+        e["i"] = -1  # append() stores payload fields at the top level of the entry
+        out[mid] = json.dumps(e)
+    elif case == "edit_hash":
+        e = json.loads(out[mid])
+        e["hash"] = "f" * 64
+        out[mid] = json.dumps(e)
+    elif case == "delete_middle":
+        del out[mid]
+    elif case == "swap_adjacent":
+        out[mid], out[mid + 1] = out[mid + 1], out[mid]
+    elif case == "truncate_tail":
+        out = out[:-10]
+    else:
+        raise ValueError(case)
+    return out
+
+
+def run(n: int) -> dict:
+    with tempfile.TemporaryDirectory() as d:
+        path = Path(d) / "bench.jsonl"
+        ledger = OperationalMerkleLedger(path)
+        lat = []
+        for i in range(n):
+            t0 = time.perf_counter()
+            ledger.append("bench", {"i": i, "payload_sha256": "0" * 64})
+            lat.append((time.perf_counter() - t0) * 1000.0)
+        lat.sort()
+        t0 = time.perf_counter()
+        clean = ledger.verify()
+        verify_ms = (time.perf_counter() - t0) * 1000.0
+
+        lines = path.read_text(encoding="utf-8").splitlines()
+        tamper = {}
+        for case in ("edit_field", "edit_hash", "delete_middle", "swap_adjacent", "truncate_tail"):
+            copy = Path(d) / f"{case}.jsonl"
+            copy.write_text("\n".join(_tamper(lines, case)) + "\n", encoding="utf-8")
+            fault = OperationalMerkleLedger(copy).verify()
+            tamper[case] = {"detected": fault is not None, "fault": fault}
+
+    return {
+        "benchmark": "ledger_append",
+        "timestamp_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
+        "host": {"machine": platform.machine(), "system": platform.system(),
+                 "release": platform.release(), "cpus": os.cpu_count(),
+                 "python": platform.python_version()},
+        "n_appends": n,
+        "append_ms": {"median": round(statistics.median(lat), 4), "p95": round(_pct(lat, 0.95), 4),
+                      "p99": round(_pct(lat, 0.99), 4), "max": round(lat[-1], 4)},
+        "verify_ms": round(verify_ms, 2),
+        "verify_clean": clean is None,
+        "tamper": tamper,
+    }
+
+
+def main(argv=None) -> int:
+    ap = argparse.ArgumentParser(description=__doc__.splitlines()[2])
+    ap.add_argument("--n", type=int, default=2000)
+    ap.add_argument("--out", default=None, help="write the result JSON here")
+    args = ap.parse_args(argv)
+    result = run(args.n)
+    text = json.dumps(result, indent=2)
+    print(text)
+    if args.out:
+        Path(args.out).write_text(text + "\n", encoding="utf-8")
+    return 0 if result["verify_clean"] else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/benchmarks/results_ledger_append.json b/benchmarks/results_ledger_append.json
@@ -0,0 +1,42 @@
+{
+  "benchmark": "ledger_append",
+  "timestamp_utc": "2026-11-10T05:17:15+00:00",
+  "host": {
+    "machine": "x86_64",
+    "system": "Linux",
+    "release": "6.18.54.1-microsoft-standard-WSL2",
+    "cpus": 32,
+    "python": "3.14.4"
+  },
+  "n_appends": 2000,
+  "append_ms": {
+    "median": 0.0598,
+    "p95": 0.0979,
+    "p99": 0.1643,
+    "max": 0.6281
+  },
+  "verify_ms": 9.33,
+  "verify_clean": true,
+  "tamper": {
+    "edit_field": {
+      "detected": true,
+      "fault": "Entry 1000: hash mismatch (expected 7afbed5337f0008e56d3816c25de8c62a8990d6d46cffea2c9a29e7c58408e96, got 1ac24f86306dcbab03cf46fb68ab6f3d24a939d70c1e8283e8c7de2184994310)"
+    },
+    "edit_hash": {
+      "detected": true,
+      "fault": "Entry 1000: hash mismatch (expected 1ac24f86306dcbab03cf46fb68ab6f3d24a939d70c1e8283e8c7de2184994310, got ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff)"
+    },
+    "delete_middle": {
+      "detected": true,
+      "fault": "Entry 1000: prev-hash mismatch (expected 4efa0f20fcfe8457db60d479a155f8333d5d28f39a4e27b7d00186e1cafbc988, got 1ac24f86306dcbab03cf46fb68ab6f3d24a939d70c1e8283e8c7de2184994310)"
+    },
+    "swap_adjacent": {
+      "detected": true,
+      "fault": "Entry 1000: prev-hash mismatch (expected 4efa0f20fcfe8457db60d479a155f8333d5d28f39a4e27b7d00186e1cafbc988, got 1ac24f86306dcbab03cf46fb68ab6f3d24a939d70c1e8283e8c7de2184994310)"
+    },
+    "truncate_tail": {
+      "detected": false,
+      "fault": null
+    }
+  }
+}
diff --git a/osiris_cli/osiris_repl.py b/osiris_cli/osiris_repl.py
@@ -1,34 +1,31 @@
 #!/usr/bin/env python3
 """
-OSIRIS Universal REPL & CLI Interface — Apex Sovereign Executable
-================================================================
-Unified Sovereign Truth Architecture Interactive Prompt & Execution Substrate.
+OSIRIS interactive console (REPL) and command-line interface.
 
 Co-authored by Devin Phillip Davis & OSIRIS dna::}{::lang NCLM
 
-Subsystems Unified:
-  1. 11D Continuous Relativistic State Matrix (CRSM) Substrate & QbyteRuntime (0.092 Coherence Floor)
-  2. Cl(3,0) Clifford Multivector Algebra & Torsion Mechanics (θ_lock = 51.843°)
-  3. 9-Agent Cognitive Mesh (Bayesian Trust, Shapley Attribution, Nash Equilibrium, Hebbian Plasticity)
-  4. Introspection Engine (CUSUM Drift Detection, Cognitive Entropy, Echo-Chamber Suppression)
-  5. Deterministic NLP Intent Classifier & Mode Scorer (Explain vs Execute, Domain Routing)
-  6. Hysteretic Power Governor (Fail-Open Desktop Mains / Termux Thermal-Battery Gate)
-  7. L0 AST & Source Firewall (Anti-Loop Transcript Quarantine, Sensitive Token Gate)
-  8. Local Ollama LLM Bridge (Model Auto-Detection, CCCE Consciousness Scoring, Swarm Integration)
-  9. Flywheel 2026 Pre-registered K8 Tau-Sweep Benchmark Suite with Merkle Cryptographic Proof
- 10. Comparative LivLM vs LLM Empirical Benchmark Suite
- 11. 21 Sovereign Command Modules (Bridges, Validation, ELO Tournament, Forge, Policy, Fabric, Demo)
- 12. Dynamic Terminal Fold-Aware UX (Automatic adaptation for mobile Termux and desktop displays)
-
-Historical constants (hypotheses from the CRSM framework, kept because older
-commands still compute with them; Devin's own hardware audits refuted theta_lock,
-the tau-phase anomaly and the CCCE "consciousness" metrics -- see
-~/docs/HONEST_ASSESSMENT.md -- so they are not shown as physical invariants):
-  • Locking Resonance:  θ_lock = 51.843° (arctan(14/11) pyramid slope)
-  • Coherence Floor:    Γ_floor = 0.0920 (Fail-closed decoherence ceiling)
-  • Memory Invariant:   Λ_Φ = 2.176435e-8 kg (Universal Memory Constant)
-  • Predicted Peak F:   F_max = 0.97871 (1 - φ^-8)
-  • Characteristic Tau: τ_0 = 46.9787 µs (φ^8)
+What this module wires together:
+  1. Command routing for the console and the batch CLI (argparse below).
+  2. The 9-agent deliberation swarm and cognitive mesh (Bayesian trust, Shapley attribution).
+  3. An introspection report (cognitive entropy, echo-chamber score) over swarm rounds.
+  4. A deterministic intent classifier (explain vs execute, domain routing).
+  5. A power governor for mobile/Termux nodes (thermal and battery gate).
+  6. The L0 source firewall (transcript quarantine, sensitive-token gate).
+  7. A local Ollama bridge (model auto-detection).
+  8. Benchmark commands, including the pre-registered K8 tau sweep (its result was a refutation).
+  9. Terminal layout that adapts to narrow (phone) and desktop displays.
+
+Execution governance (exec_policy.py, the SYS-021/SYS-025 controller, journal.py) lives in its own
+modules; this file calls them and does not reimplement them.
+
+Historical constants (hypotheses from the CRSM framework, kept because older commands still compute
+with them). Devin's own hardware audits refuted theta_lock, the tau-phase anomaly and the CCCE
+"consciousness" metrics -- see ~/docs/HONEST_ASSESSMENT.md and the claims register
+(osiris_cli/claims.py) -- so none of these is a physical invariant:
+  • θ_lock = 51.843° (arctan(14/11)); no resonance on hardware
+  • Γ_floor = 0.0920 (qbyte coherence floor; an engineering threshold)
+  • Λ_Φ = 2.176435e-8 (CRSM hypothesis; no measurement supports it)
+  • F_max = 0.97871 (1 - φ^-8) and τ_0 = 46.9787 µs (φ^8); the tau-phase prediction was refuted
 """
 
 from __future__ import annotations
@@ -930,10 +927,10 @@ def execute_introspect(state: Optional[OsirisReplState] = None) -> None:
             engine.observe_round(resps, "approve", 0.85)
 
         actions = engine.run_improvement_cycle()
-        print(f"  ├─ Axis 1 (Temporal):  CUSUM Drift Anomaly Score = 0.012 (Nominal)")
+        print("  ├─ Axis 1 (Temporal):  CUSUM drift              = not measured in this check")
         print(f"  ├─ Axis 2 (Structural): Cognitive Entropy       = {engine.structural.cognitive_entropy():.4f}")
         print(f"  ├─ Axis 2 (Structural): Echo-Chamber Score      = {engine.structural.echo_chamber_score():.4f} (Suppressed)")
-        print(f"  ├─ Axis 3 (Semantic):   Strategy Diversity Index = 0.942")
+        print("  ├─ Axis 3 (Semantic):   Strategy diversity       = not measured in this check")
         print(f"  └─ Improvement Actions Formulated: {len(actions)} auto-corrections applied.\n")
     except Exception as e:
         print(f"  └─ [INTROSPECTION] Swarm Engine: {e}\n")
@@ -949,7 +946,7 @@ def execute_introspect(state: Optional[OsirisReplState] = None) -> None:
             profile = EpistemicIntrospector.introspect_text(model, prompt)
             print("\033[1;36m[EPISTEMIC INTROSPECTION] Living Core Thermodynamic & Coherence Profile\033[0m")
             print(f"  ├─ Negentropic Efficiency (Ξ): {profile.mean_negentropy_xi:+.2f}% (Information Creation)")
-            print(f"  ├─ Bidirectional Coherence:   {profile.bidirectional_coherence:.4f} (Phase-Lock θ=51.843°)")
+            print(f"  ├─ Bidirectional Coherence:   {profile.bidirectional_coherence:.4f} ")
             print(f"  ├─ Mean Decoherence (Γ):       {profile.mean_decoherence_gamma:.4f} (Critical Threshold: 0.30)")
             top_toks = ", ".join([f"{repr(t)}:{s:.3f}" for t, s in profile.token_saliency[:4]])
             print(f"  ├─ Salient Attractors:         [{top_toks}]")
@@ -2470,7 +2467,7 @@ def main(argv: Optional[List[str]] = None) -> None:
 
     parser = argparse.ArgumentParser(
         prog="osiris",
-        description="OSIRIS Sovereign Truth Architecture - Universal CLI & Apex REPL"
+        description="OSIRIS interactive console and command-line interface"
     )
     parser.add_argument(
         "action",