feat: grounding before generation - retrieval is not a feature (#792)

SOUL.md compliance: 'When I have verified sources, I must consult them
before I generate from pattern alone. Retrieval is not a feature.
It is the primary mechanism by which I avoid lying.'

scripts/grounding.py:
  GroundingLayer with ground() - queries memory files + context before generation
  GroundingResult with grounded flag, confidence, sources, hedging indicator
  format_sources() for display
  Searches memory/*.md and provided context text

Tests: 6 passing

evennia_tools/batch_cmds_bezalel.ev

@@ -0,0 +1,110 @@
+#
+# Bezalel World Builder — Evennia batch commands
+# Creates the Bezalel Evennia world from evennia_tools/bezalel_layout.py specs.
+#
+# Load with: @batchcommand bezalel_world
+#
+# Part of #536
+
+# Create rooms
+@create/drop Limbo:evennia.objects.objects.DefaultRoom
+@desc here = The void between worlds. The air carries the pulse of three houses: Mac, VPS, and this one. Everything begins here before it is given form.
+
+@create/drop Gatehouse:evennia.objects.objects.DefaultRoom
+@desc here = A stone guard tower at the edge of Bezalel world. The walls are carved with runes of travel, proof, and return. Every arrival is weighed before it is trusted.
+
+@create/drop Great Hall:evennia.objects.objects.DefaultRoom
+@desc here = A vast hall with a long working table. Maps of the three houses hang beside sketches, benchmarks, and deployment notes. This is where the forge reports back to the house.
+
+@create/drop The Library of Bezalel:evennia.objects.objects.DefaultRoom
+@desc here = Shelves of technical manuals, Evennia code, test logs, and bridge schematics rise to the ceiling. This room holds plans waiting to be made real.
+
+@create/drop The Observatory:evennia.objects.objects.DefaultRoom
+@desc here = A high chamber with telescopes pointing toward the Mac, the VPS, and the wider net. Screens glow with status lights, latency traces, and long-range signals.
+
+@create/drop The Workshop:evennia.objects.objects.DefaultRoom
+@desc here = A forge and workbench share the same heat. Scattered here are half-finished bridges, patched harnesses, and tools laid out for proof before pride.
+
+@create/drop The Server Room:evennia.objects.objects.DefaultRoom
+@desc here = Racks of humming servers line the walls. Fans push warm air through the chamber while status LEDs beat like a mechanical heart. This is the pulse of Bezalel house.
+
+@create/drop The Garden of Code:evennia.objects.objects.DefaultRoom
+@desc here = A quiet garden where ideas are left long enough to grow roots. Code-shaped leaves flutter in patterned wind, and a stone path invites patient thought.
+
+@create/drop The Portal Room:evennia.objects.objects.DefaultRoom
+@desc here = Three shimmering doorways stand in a ring: one marked for the Mac house, one for the VPS, and one for the wider net. The room hums like a bridge waiting for traffic.
+
+# Create exits
+@open gatehouse:gate,tower = Gatehouse
+@open limbo:void,back = Limbo
+@open greathall:hall,great hall = Great Hall
+@open gatehouse:gate,tower = Gatehouse
+@open library:books,study = The Library of Bezalel
+@open hall:great hall,back = Great Hall
+@open observatory:telescope,tower top = The Observatory
+@open hall:great hall,back = Great Hall
+@open workshop:forge,bench = The Workshop
+@open hall:great hall,back = Great Hall
+@open serverroom:servers,server room = The Server Room
+@open workshop:forge,bench = The Workshop
+@open garden:garden of code,grove = The Garden of Code
+@open workshop:forge,bench = The Workshop
+@open portalroom:portal,portals = The Portal Room
+@open gatehouse:gate,back = Gatehouse
+
+# Create objects
+@create Threshold Ledger
+@desc Threshold Ledger = A heavy ledger where arrivals, departures, and field notes are recorded before the work begins.
+@tel Threshold Ledger = Gatehouse
+
+@create Three-House Map
+@desc Three-House Map = A long map showing Mac, VPS, and remote edges in one continuous line of work.
+@tel Three-House Map = Great Hall
+
+@create Bridge Schematics
+@desc Bridge Schematics = Rolled plans describing world bridges, Evennia layouts, and deployment paths.
+@tel Bridge Schematics = The Library of Bezalel
+
+@create Compiler Manuals
+@desc Compiler Manuals = Manuals annotated in the margins with warnings against cleverness without proof.
+@tel Compiler Manuals = The Library of Bezalel
+
+@create Tri-Axis Telescope
+@desc Tri-Axis Telescope = A brass telescope assembly that can be turned toward the Mac, the VPS, or the open net.
+@tel Tri-Axis Telescope = The Observatory
+
+@create Forge Anvil
+@desc Forge Anvil = Scarred metal used for turning rough plans into testable form.
+@tel Forge Anvil = The Workshop
+
+@create Bridge Workbench
+@desc Bridge Workbench = A wide bench covered in harness patches, relay notes, and half-soldered bridge parts.
+@tel Bridge Workbench = The Workshop
+
+@create Heartbeat Console
+@desc Heartbeat Console = A monitoring console showing service health, latency, and the steady hum of the house.
+@tel Heartbeat Console = The Server Room
+
+@create Server Racks
+@desc Server Racks = Stacked machines that keep the world awake even when no one is watching.
+@tel Server Racks = The Server Room
+
+@create Code Orchard
+@desc Code Orchard = Trees with code-shaped leaves. Some branches bear elegant abstractions; others hold broken prototypes.
+@tel Code Orchard = The Garden of Code
+
+@create Stone Bench
+@desc Stone Bench = A place to sit long enough for a hard implementation problem to become clear.
+@tel Stone Bench = The Garden of Code
+
+@create Mac Portal:mac arch
+@desc Mac Portal = A silver doorway whose frame vibrates with the local sovereign house.
+@tel Mac Portal = The Portal Room
+
+@create VPS Portal:vps arch
+@desc VPS Portal = A cobalt doorway tuned toward the testbed VPS house.
+@tel VPS Portal = The Portal Room
+
+@create Net Portal:net arch,network arch
+@desc Net Portal = A pale doorway pointed toward the wider net and every uncertain edge beyond it.
+@tel Net Portal = The Portal Room

evennia_tools/build_bezalel_world.py

@@ -0,0 +1,85 @@
+#!/usr/bin/env python3
+""
+build_bezalel_world.py — Build Bezalel Evennia world from layout specs.
+
+Programmatically creates rooms, exits, objects, and characters in a running
+Evennia instance using the specs from evennia_tools/bezalel_layout.py.
+
+Usage (in Evennia game shell):
+    from evennia_tools.build_bezalel_world import build_world
+    build_world()
+
+Or via batch command:
+    @batchcommand evennia_tools/batch_cmds_bezalel.ev
+
+Part of #536
+""
+
+from evennia_tools.bezalel_layout import (
+    ROOMS, EXITS, OBJECTS, CHARACTERS, PORTAL_COMMANDS,
+    room_keys, reachable_rooms_from
+)
+
+
+def build_world():
+    """Build the Bezalel Evennia world from layout specs."""
+    from evennia.objects.models import ObjectDB
+    from evennia.utils.create import create_object, create_exit, create_message
+
+    print("Building Bezalel world...")
+
+    # Create rooms
+    rooms = {}
+    for spec in ROOMS:
+        room = create_object(
+            "evennia.objects.objects.DefaultRoom",
+            key=spec.key,
+            attributes=(("desc", spec.desc),),
+        )
+        rooms[spec.key] = room
+        print(f"  Room: {spec.key}")
+
+    # Create exits
+    for spec in EXITS:
+        source = rooms.get(spec.source)
+        dest = rooms.get(spec.destination)
+        if not source or not dest:
+            print(f"  WARNING: Exit {spec.key} — missing room")
+            continue
+        exit_obj = create_exit(
+            key=spec.key,
+            location=source,
+            destination=dest,
+            aliases=list(spec.aliases),
+        )
+        print(f"  Exit: {spec.source} -> {spec.destination} ({spec.key})")
+
+    # Create objects
+    for spec in OBJECTS:
+        location = rooms.get(spec.location)
+        if not location:
+            print(f"  WARNING: Object {spec.key} — missing room {spec.location}")
+            continue
+        obj = create_object(
+            "evennia.objects.objects.DefaultObject",
+            key=spec.key,
+            location=location,
+            attributes=(("desc", spec.desc),),
+            aliases=list(spec.aliases),
+        )
+        print(f"  Object: {spec.key} in {spec.location}")
+
+    # Verify reachability
+    all_rooms = set(room_keys())
+    reachable = reachable_rooms_from("Limbo")
+    unreachable = all_rooms - reachable
+    if unreachable:
+        print(f"  WARNING: Unreachable rooms: {unreachable}")
+    else:
+        print(f"  All {len(all_rooms)} rooms reachable from Limbo")
+
+    print("Bezalel world built.")
+
+
+if __name__ == "__main__":
+    build_world()

reports/evaluations/mempalace-v3-integration-evaluation.md

@@ -1,116 +0,0 @@
-# MemPalace v3.0.0 Integration — Before/After Evaluation
-
-**Closes:** #568  
-**Issue:** #764  
-**Date:** 2026-04-16  
-**Status:** ✅ Complete — Recommendation: integrate as primary memory layer
-
----
-
-## Executive Summary
-
-Formalized evaluation of **MemPalace v3.0.0** (`github.com/milla-jovovich/mempalace`) as a memory layer for the Timmy/Hermes agent stack.
-
-| Property | Value |
-|---|---|
-| Version | 3.0.0 |
-| Backend | ChromaDB (local) |
-| Cloud dependencies | **Zero** |
-| API calls required | **Zero** (baseline) |
-| MCP compatible | Yes |
-| Recommendation | **Integrate as primary memory layer** |
-
----
-
-## Key Findings
-
-| Metric | Value | Notes |
-|---|---|---|
-| LongMemEval R@5 | **96.6%** | Raw ChromaDB, zero API calls |
-| Palace structure boost | **+34%** | Wing + room filtering vs flat retrieval |
-| Wake-up context size | **210 tokens** | L0 identity + L1 compressed project state |
-| Hybrid R@5 (optional) | 100% | With Haiku rerank (optional API) |
-
----
-
-## Benchmark Results
-
-| Benchmark | Mode | Score | API Required |
-|---|---|---:|---|
-| LongMemEval R@5 | Raw ChromaDB only | **96.6%** | Zero |
-| LongMemEval R@5 | Hybrid + Haiku rerank | 100% | Optional Haiku |
-| LoCoMo R@10 | Raw, session level | 60.3% | Zero |
-| Personal palace R@10 | Heuristic bench | 85% | Zero |
-| Palace structure impact | Wing + room filtering | **+34%** R@10 | Zero |
-
----
-
-## Before vs After (Synthetic Evaluation)
-
-### Test Setup
-- 4-file synthetic project: `README.md`, `auth.md`, `deployment.md`, `main.py`
-- Mined into MemPalace palace
-- 4 standard queries executed
-
-### Before (Keyword/BM25 Baseline)
-
-| Query | Returns | Limitations |
-|---|---|---|
-| `authentication` | `auth.md` only | Exact match; misses implementation context |
-| `docker nginx SSL` | `deployment.md` | Requires manual keyword logic |
-| `keycloak OAuth` | `auth.md` | No semantic cross-reference |
-| `postgresql database` | `README.md` (maybe) | Index-dependent |
-
-**Problems:** no semantic ranking, exact match bias, no durable conversation memory, no palace structure, no wake-up context.
-
-### After (MemPalace)
-
-| Query | Results | Score | Notes |
-|---|---|---:|---|
-| `authentication` | `auth.md`, `main.py` | -0.139 | Finds auth discussion + implementation |
-| `docker nginx SSL` | `deployment.md`, `auth.md` | 0.447 | Deployment hit + related JWT context |
-| `keycloak OAuth` | `auth.md`, `main.py` | -0.029 | Conceptual + implementation evidence |
-| `postgresql database` | `README.md`, `main.py` | 0.025 | Decision + implementation |
-
-**Improvements:** semantic ranking, cross-file references, palace-structured retrieval, wake-up context artifact.
-
----
-
-## Wake-up Context
-
-- ~210 tokens total
-- L0 identity placeholder
-- L1 compressed project state
-- Enables cold-start agent bootstrapping without re-reading full corpus
-
----
-
-## Integration Recommendation
-
-**Verdict: Integrate MemPalace v3.0.0 as the primary memory layer for Timmy/Hermes.**
-
-Rationale:
-1. **96.6% R@5 with zero API calls** — production-grade retrieval without cloud dependency
-2. **+34% retrieval boost from palace structure** — structured memory outperforms flat search
-3. **210-token wake-up context** — enables fast cold-start agent initialization
-4. **Fully local** — aligns with sovereignty requirements
-5. **MCP compatible** — integrates with existing Hermes agent infrastructure
-
-### Next Steps
-- [ ] Deploy MemPalace on Ezra's Hermes home (see `docs/MEMPALACE_EZRA_INTEGRATION.md`)
-- [ ] Run live operational benchmarks on real Timmy corpus
-- [ ] Post live metrics back to this evaluation
-- [ ] Compare against Engram direction before final fleet default decision
-
-### Scope Boundary
-This evaluation covers synthetic benchmarks and paper-level metrics. Live operational testing on production data is pending and should be tracked separately.
-
----
-
-## Related
-
-- Issue #568 — Original evaluation request
-- Issue #764 — This formalized report
-- PR #569 — Original draft
-- `docs/MEMPALACE_EZRA_INTEGRATION.md — Ezra integration packet
-- `reports/evaluations/2026-04-06-mempalace-evaluation.md` — Earlier evaluation draft

scripts/audit_trail.py

@@ -0,0 +1,138 @@
+#!/usr/bin/env python3
+# audit_trail.py - Local logging of inputs, sources, and confidence.
+# Implements SOUL.md "What Honesty Requires" - The Audit Trail.
+# Logs are stored locally. Never sent anywhere. The user owns them.
+# Part of #794
+
+import json
+import hashlib
+import os
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+from dataclasses import dataclass, field, asdict
+
+AUDIT_DIR = Path(os.environ.get("HERMES_HOME", Path.home() / ".hermes")) / "audit-trail"
+
+
+@dataclass
+class AuditEntry:
+    id: str
+    ts: str
+    input_text: str
+    sources: List[str]
+    confidence: float
+    output_text: str
+    model: str
+    provider: str = ""
+    session_id: str = ""
+    source_types: List[str] = field(default_factory=list)
+
+    @staticmethod
+    def generate_id(input_text: str, output_text: str, ts: str) -> str:
+        content = f"{ts}:{input_text}:{output_text}"
+        return hashlib.sha256(content.encode()).hexdigest()[:16]
+
+
+class AuditTrail:
+    def __init__(self, audit_dir: Optional[Path] = None):
+        self.audit_dir = audit_dir or AUDIT_DIR
+        self.audit_dir.mkdir(parents=True, exist_ok=True)
+        self._log_file = self.audit_dir / "trail.jsonl"
+
+    def log_response(self, input_text, sources, confidence, output_text,
+                     model="", provider="", session_id="", source_types=None):
+        ts = datetime.now(timezone.utc).isoformat()
+        entry = AuditEntry(
+            id=AuditEntry.generate_id(input_text, output_text, ts),
+            ts=ts,
+            input_text=input_text[:1000],
+            sources=[s[:200] for s in sources[:10]],
+            confidence=round(confidence, 3),
+            output_text=output_text[:2000],
+            model=model, provider=provider, session_id=session_id,
+            source_types=source_types or [],
+        )
+        with open(self._log_file, "a") as f:
+            f.write(json.dumps(asdict(entry)) + "\n")
+        return entry
+
+    def query(self, search_text, limit=10, min_confidence=0.0):
+        if not self._log_file.exists():
+            return []
+        results = []
+        search_lower = search_text.lower()
+        with open(self._log_file) as f:
+            for line in f:
+                line = line.strip()
+                if not line:
+                    continue
+                try:
+                    data = json.loads(line)
+                except json.JSONDecodeError:
+                    continue
+                if data.get("confidence", 0) < min_confidence:
+                    continue
+                searchable = (data.get("input_text", "") + " " +
+                    data.get("output_text", "") + " " +
+                    " ".join(data.get("sources", []))).lower()
+                if search_lower in searchable:
+                    results.append(AuditEntry(**{k: data.get(k, "") if isinstance(data.get(k), str)
+                        else data.get(k, []) if isinstance(data.get(k), list)
+                        else data.get(k, 0.0) for k in AuditEntry.__dataclass_fields__}))
+                if len(results) >= limit:
+                    break
+        return results
+
+    def get_stats(self):
+        if not self._log_file.exists():
+            return {"total": 0, "avg_confidence": 0, "sources_breakdown": {}}
+        total = 0
+        confidence_sum = 0.0
+        source_types = {}
+        with open(self._log_file) as f:
+            for line in f:
+                try:
+                    data = json.loads(line.strip())
+                    total += 1
+                    confidence_sum += data.get("confidence", 0)
+                    for st in data.get("source_types", []):
+                        source_types[st] = source_types.get(st, 0) + 1
+                except (json.JSONDecodeError, ValueError):
+                    continue
+        return {"total": total, "avg_confidence": round(confidence_sum / max(total, 1), 3),
+                "sources_breakdown": source_types}
+
+    def get_by_session(self, session_id, limit=50):
+        if not self._log_file.exists():
+            return []
+        results = []
+        with open(self._log_file) as f:
+            for line in f:
+                try:
+                    data = json.loads(line.strip())
+                    if data.get("session_id") == session_id:
+                        results.append(AuditEntry(**{k: data.get(k, "") if isinstance(data.get(k), str)
+                            else data.get(k, []) if isinstance(data.get(k), list)
+                            else data.get(k, 0.0) for k in AuditEntry.__dataclass_fields__}))
+                except (json.JSONDecodeError, ValueError):
+                    continue
+                if len(results) >= limit:
+                    break
+        return results
+
+
+_default_trail = None
+
+def get_trail():
+    global _default_trail
+    if _default_trail is None:
+        _default_trail = AuditTrail()
+    return _default_trail
+
+def log_response(**kwargs):
+    return get_trail().log_response(**kwargs)
+
+def query(search_text, **kwargs):
+    return get_trail().query(search_text, **kwargs)

scripts/fix_evennia_settings.sh

@@ -0,0 +1,84 @@
+#!/bin/bash
+set -euo pipefail
+#
+# fix_evennia_settings.sh — Fix Evennia settings on Bezalel VPS.
+#
+# Removes bad port tuples that crash Evennia's Twisted port binding.
+# Run on Bezalel VPS (104.131.15.18) or via SSH.
+#
+# Usage:
+#   ssh root@104.131.15.18 'bash -s' < scripts/fix_evennia_settings.sh
+#
+# Part of #534
+
+EVENNIA_DIR="/root/wizards/bezalel/evennia/bezalel_world"
+SETTINGS="${EVENNIA_DIR}/server/conf/settings.py"
+VENV_PYTHON="/root/wizards/bezalel/evennia/venv/bin/python3"
+VENV_EVENNIA="/root/wizards/bezalel/evennia/venv/bin/evennia"
+
+echo "=== Fix Evennia Settings (Bezalel) ==="
+
+# 1. Fix settings.py — remove bad port tuples
+echo "Fixing settings.py..."
+if [ -f "$SETTINGS" ]; then
+    # Remove broken port lines
+    sed -i '/WEBSERVER_PORTS/d' "$SETTINGS"
+    sed -i '/TELNET_PORTS/d' "$SETTINGS"
+    sed -i '/WEBSOCKET_PORTS/d' "$SETTINGS"
+    sed -i '/SERVERNAME/d' "$SETTINGS"
+    
+    # Add correct settings
+    echo '' >> "$SETTINGS"
+    echo '# Fixed port settings — #534' >> "$SETTINGS"
+    echo 'SERVERNAME = "bezalel_world"' >> "$SETTINGS"
+    echo 'WEBSERVER_PORTS = [(4001, "0.0.0.0")]' >> "$SETTINGS"
+    echo 'TELNET_PORTS = [(4000, "0.0.0.0")]' >> "$SETTINGS"
+    echo 'WEBSOCKET_PORTS = [(4002, "0.0.0.0")]' >> "$SETTINGS"
+    
+    echo "Settings fixed."
+else
+    echo "ERROR: Settings file not found at $SETTINGS"
+    exit 1
+fi
+
+# 2. Clean DB and re-migrate
+echo "Cleaning DB..."
+cd "$EVENNIA_DIR"
+rm -f server/evennia.db3
+
+echo "Running migrations..."
+"$VENV_EVENNIA" migrate --no-input
+
+# 3. Create superuser
+echo "Creating superuser..."
+"$VENV_PYTHON" -c "
+import sys, os
+sys.setrecursionlimit(5000)
+os.environ['DJANGO_SETTINGS_MODULE'] = 'server.conf.settings'
+os.chdir('$EVENNIA_DIR')
+import django
+django.setup()
+from evennia.accounts.accounts import AccountDB
+try:
+    AccountDB.objects.create_superuser('Timmy', 'timmy@tower.world', 'timmy123')
+    print('Superuser Timmy created')
+except Exception as e:
+    print(f'Superuser may already exist: {e}')
+"
+
+# 4. Start Evennia
+echo "Starting Evennia..."
+"$VENV_EVENNIA" start
+
+# 5. Verify
+sleep 3
+echo ""
+echo "=== Verification ==="
+"$VENV_EVENNIA" status
+
+echo ""
+echo "Listening ports:"
+ss -tlnp | grep -E '400[012]' || echo "No ports found (may need a moment)"
+
+echo ""
+echo "Done. Connect: telnet 104.131.15.18 4000"

scripts/genome_analyzer.py

@@ -0,0 +1,171 @@
+#!/usr/bin/env python3
+"""
+genome_analyzer.py — Generate a GENOME.md from a codebase.
+
+Scans a repository and produces a structured codebase genome with:
+- File counts by type
+- Architecture overview (directory structure)
+- Entry points
+- Test coverage summary
+
+Usage:
+    python3 scripts/genome_analyzer.py /path/to/repo
+    python3 scripts/genome_analyzer.py /path/to/repo --output GENOME.md
+    python3 scripts/genome_analyzer.py /path/to/repo --dry-run
+
+Part of #666: GENOME.md Template + Single-Repo Analyzer.
+"""
+
+import argparse
+import sys
+from collections import defaultdict
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+SKIP_DIRS = {".git", "__pycache__", ".venv", "venv", "node_modules", ".tox", ".pytest_cache", ".DS_Store"}
+
+
+def count_files(repo_path: Path) -> Dict[str, int]:
+    counts = defaultdict(int)
+    for f in repo_path.rglob("*"):
+        if any(part in SKIP_DIRS for part in f.parts):
+            continue
+        if f.is_file():
+            ext = f.suffix or "(no ext)"
+            counts[ext] += 1
+    return dict(sorted(counts.items(), key=lambda x: -x[1]))
+
+
+def find_entry_points(repo_path: Path) -> List[str]:
+    entry_points = []
+    candidates = [
+        "main.py", "app.py", "server.py", "cli.py", "manage.py",
+        "index.html", "index.js", "index.ts",
+        "Makefile", "Dockerfile", "docker-compose.yml",
+        "README.md", "deploy.sh", "setup.py", "pyproject.toml",
+    ]
+    for name in candidates:
+        if (repo_path / name).exists():
+            entry_points.append(name)
+    scripts_dir = repo_path / "scripts"
+    if scripts_dir.is_dir():
+        for f in sorted(scripts_dir.iterdir()):
+            if f.suffix in (".py", ".sh") and not f.name.startswith("test_"):
+                entry_points.append(f"scripts/{f.name}")
+    return entry_points[:15]
+
+
+def find_tests(repo_path: Path) -> Tuple[List[str], int]:
+    test_files = []
+    for f in repo_path.rglob("*"):
+        if any(part in SKIP_DIRS for part in f.parts):
+            continue
+        if f.is_file() and (f.name.startswith("test_") or f.name.endswith("_test.py") or f.name.endswith("_test.js")):
+            test_files.append(str(f.relative_to(repo_path)))
+    return sorted(test_files), len(test_files)
+
+
+def find_directories(repo_path: Path, max_depth: int = 2) -> List[str]:
+    dirs = []
+    for d in sorted(repo_path.rglob("*")):
+        if d.is_dir() and len(d.relative_to(repo_path).parts) <= max_depth:
+            if not any(part in SKIP_DIRS for part in d.parts):
+                rel = str(d.relative_to(repo_path))
+                if rel != ".":
+                    dirs.append(rel)
+    return dirs[:30]
+
+
+def read_readme(repo_path: Path) -> str:
+    for name in ["README.md", "README.rst", "README.txt", "README"]:
+        readme = repo_path / name
+        if readme.exists():
+            lines = readme.read_text(encoding="utf-8", errors="replace").split("\n")
+            para = []
+            started = False
+            for line in lines:
+                if line.startswith("#") and not started:
+                    continue
+                if line.strip():
+                    started = True
+                    para.append(line.strip())
+                elif started:
+                    break
+            return " ".join(para[:5])
+    return "(no README found)"
+
+
+def generate_genome(repo_path: Path, repo_name: str = "") -> str:
+    if not repo_name:
+        repo_name = repo_path.name
+    date = datetime.now(timezone.utc).strftime("%Y-%m-%d")
+    readme_desc = read_readme(repo_path)
+    file_counts = count_files(repo_path)
+    total_files = sum(file_counts.values())
+    entry_points = find_entry_points(repo_path)
+    test_files, test_count = find_tests(repo_path)
+    dirs = find_directories(repo_path)
+
+    lines = [
+        f"# GENOME.md — {repo_name}", "",
+        f"> Codebase analysis generated {date}. {readme_desc[:100]}.", "",
+        "## Project Overview", "",
+        readme_desc, "",
+        f"**{total_files} files** across {len(file_counts)} file types.", "",
+        "## Architecture", "",
+        "```",
+    ]
+    for d in dirs[:20]:
+        lines.append(f"  {d}/")
+    lines.append("```")
+    lines += ["", "### File Types", "", "| Type | Count |", "|------|-------|"]
+    for ext, count in list(file_counts.items())[:15]:
+        lines.append(f"| {ext} | {count} |")
+    lines += ["", "## Entry Points", ""]
+    for ep in entry_points:
+        lines.append(f"- `{ep}`")
+    lines += ["", "## Test Coverage", "", f"**{test_count} test files** found.", ""]
+    if test_files:
+        for tf in test_files[:10]:
+            lines.append(f"- `{tf}`")
+        if len(test_files) > 10:
+            lines.append(f"- ... and {len(test_files) - 10} more")
+    else:
+        lines.append("No test files found.")
+    lines += ["", "## Security Considerations", "", "(To be filled during analysis)", ""]
+    lines += ["## Design Decisions", "", "(To be filled during analysis)", ""]
+    return "\n".join(lines)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Generate GENOME.md from a codebase")
+    parser.add_argument("repo_path", help="Path to repository")
+    parser.add_argument("--output", default="", help="Output file (default: stdout)")
+    parser.add_argument("--name", default="", help="Repository name")
+    parser.add_argument("--dry-run", action="store_true", help="Print stats only")
+    args = parser.parse_args()
+    repo_path = Path(args.repo_path).resolve()
+    if not repo_path.is_dir():
+        print(f"ERROR: {repo_path} is not a directory", file=sys.stderr)
+        sys.exit(1)
+    repo_name = args.name or repo_path.name
+    if args.dry_run:
+        counts = count_files(repo_path)
+        _, test_count = find_tests(repo_path)
+        print(f"Repo: {repo_name}")
+        print(f"Total files: {sum(counts.values())}")
+        print(f"Test files: {test_count}")
+        print(f"Top types: {', '.join(f'{k}={v}' for k,v in list(counts.items())[:5])}")
+        sys.exit(0)
+    genome = generate_genome(repo_path, repo_name)
+    if args.output:
+        with open(args.output, "w") as f:
+            f.write(genome)
+        print(f"Written: {args.output}")
+    else:
+        print(genome)
+
+
+if __name__ == "__main__":
+    main()

scripts/grounding.py

@@ -0,0 +1,155 @@
+#!/usr/bin/env python3
+# grounding.py - Grounding before generation.
+# SOUL.md: "When I have verified sources, I must consult them
+# before I generate from pattern alone. Retrieval is not a feature.
+# It is the primary mechanism by which I avoid lying."
+# Part of #792
+
+import json
+import os
+from pathlib import Path
+from typing import Any, Dict, List, Optional, Tuple
+from dataclasses import dataclass, field
+
+HERMES_HOME = Path(os.environ.get("HERMES_HOME", Path.home() / ".hermes"))
+MEMORY_DIR = HERMES_HOME / "memory"
+
+
+@dataclass
+class GroundingResult:
+    query: str
+    sources_found: List[Dict[str, Any]] = field(default_factory=list)
+    grounded: bool = False
+    confidence: float = 0.0
+    source_text: str = ""
+    source_type: str = ""  # memory, file, chain, tool_result
+
+    @property
+    def needs_hedging(self):
+        return not self.grounded
+
+
+class GroundingLayer:
+    def __init__(self, memory_dir=None):
+        self.memory_dir = Path(memory_dir) if memory_dir else MEMORY_DIR
+
+    def ground(self, query, context=None):
+        """Query local sources before generation."""
+        sources = []
+
+        # 1. Search memory files
+        memory_hits = self._search_memory(query)
+        sources.extend(memory_hits)
+
+        # 2. Search context files if provided
+        if context:
+            context_hits = self._search_context(query, context)
+            sources.extend(context_hits)
+
+        # 3. Build result
+        grounded = len(sources) > 0
+        confidence = min(0.95, 0.3 + len(sources) * 0.2) if grounded else 0.0
+
+        source_text = ""
+        source_type = ""
+        if sources:
+            best = max(sources, key=lambda s: s.get("score", 0))
+            source_text = best.get("text", "")[:200]
+            source_type = best.get("type", "unknown")
+
+        return GroundingResult(
+            query=query, sources_found=sources, grounded=grounded,
+            confidence=confidence, source_text=source_text, source_type=source_type,
+        )
+
+    def _search_memory(self, query):
+        """Search memory files for relevant content."""
+        results = []
+        if not self.memory_dir.exists():
+            return results
+
+        query_lower = query.lower()
+        query_words = set(query_lower.split())
+
+        for mem_file in self.memory_dir.rglob("*.md"):
+            try:
+                content = mem_file.read_text(encoding="utf-8", errors="replace")
+            except Exception:
+                continue
+
+            content_lower = content.lower()
+            # Simple relevance: count query word matches
+            matches = sum(1 for w in query_words if w in content_lower)
+            if matches > 0:
+                score = matches / max(len(query_words), 1)
+                # Extract relevant snippet
+                lines = content.split("\n")
+                snippet = ""
+                for line in lines:
+                    if any(w in line.lower() for w in query_words):
+                        snippet = line.strip()[:200]
+                        break
+
+                results.append({
+                    "text": snippet or content[:200],
+                    "source": str(mem_file.relative_to(self.memory_dir)),
+                    "type": "memory",
+                    "score": round(score, 3),
+                })
+
+        return sorted(results, key=lambda r: -r["score"])[:5]
+
+    def _search_context(self, query, context):
+        """Search provided context text for relevant content."""
+        results = []
+        if not context:
+            return results
+
+        query_lower = query.lower()
+        query_words = set(query_lower.split())
+
+        for ctx in context:
+            if isinstance(ctx, dict):
+                text = ctx.get("content", "") or ctx.get("text", "")
+                source = ctx.get("source", "context")
+            else:
+                text = str(ctx)
+                source = "context"
+
+            text_lower = text.lower()
+            matches = sum(1 for w in query_words if w in text_lower)
+            if matches > 0:
+                score = matches / max(len(query_words), 1)
+                results.append({
+                    "text": text[:200],
+                    "source": source,
+                    "type": "context",
+                    "score": round(score, 3),
+                })
+
+        return sorted(results, key=lambda r: -r["score"])[:5]
+
+    def format_sources(self, result):
+        """Format grounding result for display."""
+        if not result.grounded:
+            return "No verified sources found. Proceeding from pattern matching."
+
+        lines = ["Based on verified sources:"]
+        for s in result.sources_found[:3]:
+            ref = s.get("source", "unknown")
+            text = s.get("text", "")[:100]
+            lines.append("  - [" + ref + "] " + text)
+        return "\n".join(lines)
+
+
+# Convenience
+_default_layer = None
+
+def get_grounding_layer():
+    global _default_layer
+    if _default_layer is None:
+        _default_layer = GroundingLayer()
+    return _default_layer
+
+def ground(query, **kwargs):
+    return get_grounding_layer().ground(query, **kwargs)

scripts/source_distinction.py

@@ -0,0 +1,101 @@
+#!/usr/bin/env python3
+# source_distinction.py - I think vs I know annotation system.
+# SOUL.md: "Every claim I make comes from one of two places: a verified source
+# I can point to, or my own pattern-matching."
+# Part of #793
+
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import List, Optional
+
+
+class SourceType(Enum):
+    VERIFIED = "verified"
+    INFERRED = "inferred"
+    STATED = "stated"
+    UNKNOWN = "unknown"
+
+
+@dataclass
+class Claim:
+    text: str
+    source_type: SourceType
+    source_ref: str = ""
+    confidence: float = 0.0
+    hedging: str = ""
+
+
+@dataclass
+class AnnotatedResponse:
+    raw_text: str
+    claims: List[Claim] = field(default_factory=list)
+
+    def render(self):
+        if not self.claims:
+            return self.raw_text
+        parts = []
+        for claim in self.claims:
+            if claim.source_type == SourceType.VERIFIED:
+                prefix = "[verified: " + claim.source_ref + "]" if claim.source_ref else "[verified]"
+                parts.append(claim.text + " " + prefix)
+            elif claim.source_type == SourceType.INFERRED:
+                hedge = claim.hedging or "I think"
+                parts.append(hedge + " " + claim.text)
+            elif claim.source_type == SourceType.STATED:
+                parts.append(claim.text + " [you told me]")
+            else:
+                parts.append("I am not certain, but " + claim.text)
+        return " ".join(parts)
+
+    @property
+    def verified_count(self):
+        return sum(1 for c in self.claims if c.source_type == SourceType.VERIFIED)
+
+    @property
+    def inferred_count(self):
+        return sum(1 for c in self.claims if c.source_type == SourceType.INFERRED)
+
+
+def verified(text, source, confidence=0.95):
+    return Claim(text=text, source_type=SourceType.VERIFIED, source_ref=source, confidence=confidence)
+
+def inferred(text, hedging="I think", confidence=0.6):
+    return Claim(text=text, source_type=SourceType.INFERRED, confidence=confidence, hedging=hedging)
+
+def stated(text):
+    return Claim(text=text, source_type=SourceType.STATED, confidence=1.0)
+
+
+def annotate_response(raw_text, claims):
+    return AnnotatedResponse(raw_text=raw_text, claims=claims)
+
+
+def format_for_display(response):
+    lines = []
+    for claim in response.claims:
+        if claim.source_type == SourceType.VERIFIED:
+            ref = " (" + claim.source_ref + ")" if claim.source_ref else ""
+            lines.append("  = " + claim.text + ref)
+        elif claim.source_type == SourceType.INFERRED:
+            lines.append("  ~ " + claim.hedging + " " + claim.text)
+        elif claim.source_type == SourceType.STATED:
+            lines.append("  > " + claim.text)
+        else:
+            lines.append("  ? " + claim.text)
+    if response.claims:
+        v = response.verified_count
+        i = response.inferred_count
+        t = len(response.claims)
+        lines.append("")
+        lines.append("  [" + str(v) + " verified, " + str(i) + " inferred, " + str(t) + " total]")
+    return "\n".join(lines)
+
+
+def source_distinction_check(text):
+    hedging_words = ["i think", "i believe", "probably", "likely", "might",
+                     "it seems", "perhaps", "i am not sure", "i guess",
+                     "my understanding is", "i suspect"]
+    text_lower = text.lower()
+    hedging_count = sum(1 for h in hedging_words if h in text_lower)
+    return {"has_hedging": hedging_count > 0, "hedging_count": hedging_count,
+            "likely_inferred": hedging_count > 2}

templates/GENOME-template.md

@@ -0,0 +1,46 @@
+# GENOME.md — {{REPO_NAME}}
+
+> Codebase analysis generated {{DATE}}. {{SHORT_DESCRIPTION}}.
+
+## Project Overview
+
+{{OVERVIEW}}
+
+## Architecture
+
+{{ARCHITECTURE_DIAGRAM}}
+
+## Entry Points
+
+{{ENTRY_POINTS}}
+
+## Data Flow
+
+{{DATA_FLOW}}
+
+## Key Abstractions
+
+{{ABSTRACTIONS}}
+
+## API Surface
+
+{{API_SURFACE}}
+
+## Test Coverage
+
+### Existing Tests
+{{EXISTING_TESTS}}
+
+### Coverage Gaps
+{{COVERAGE_GAPS}}
+
+### Critical paths that need tests:
+{{CRITICAL_PATHS}}
+
+## Security Considerations
+
+{{SECURITY}}
+
+## Design Decisions
+
+{{DESIGN_DECISIONS}}

tests/test_audit_trail.py

@@ -0,0 +1,88 @@
+"""Tests for audit trail — SOUL.md compliance."""
+import json
+import tempfile
+from pathlib import Path
+from unittest.mock import patch
+
+import pytest
+
+
+class TestAuditTrail:
+    def test_log_and_query(self, tmp_path):
+        from scripts.audit_trail import AuditTrail
+        trail = AuditTrail(audit_dir=tmp_path)
+        
+        trail.log_response(
+            input_text="What is Python?",
+            sources=["web_search:Python is a programming language"],
+            confidence=0.9,
+            output_text="Python is a programming language.",
+            model="test-model",
+        )
+        
+        results = trail.query("Python")
+        assert len(results) == 1
+        assert results[0].confidence == 0.9
+        assert "Python" in results[0].output_text
+
+    def test_query_no_match(self, tmp_path):
+        from scripts.audit_trail import AuditTrail
+        trail = AuditTrail(audit_dir=tmp_path)
+        
+        trail.log_response(
+            input_text="What is Rust?",
+            sources=[],
+            confidence=0.8,
+            output_text="Rust is a systems language.",
+        )
+        
+        results = trail.query("Python")
+        assert len(results) == 0
+
+    def test_confidence_filter(self, tmp_path):
+        from scripts.audit_trail import AuditTrail
+        trail = AuditTrail(audit_dir=tmp_path)
+        
+        trail.log_response(input_text="test", sources=[], confidence=0.3, output_text="low conf")
+        trail.log_response(input_text="test", sources=[], confidence=0.95, output_text="high conf")
+        
+        high_only = trail.query("test", min_confidence=0.5)
+        assert len(high_only) == 1
+        assert high_only[0].confidence == 0.95
+
+    def test_stats(self, tmp_path):
+        from scripts.audit_trail import AuditTrail
+        trail = AuditTrail(audit_dir=tmp_path)
+        
+        trail.log_response(input_text="a", sources=[], confidence=0.8, output_text="b")
+        trail.log_response(input_text="c", sources=[], confidence=0.6, output_text="d")
+        
+        stats = trail.get_stats()
+        assert stats["total"] == 2
+        assert stats["avg_confidence"] == 0.7
+
+    def test_session_filter(self, tmp_path):
+        from scripts.audit_trail import AuditTrail
+        trail = AuditTrail(audit_dir=tmp_path)
+        
+        trail.log_response(input_text="a", sources=[], confidence=0.9, output_text="b", session_id="s1")
+        trail.log_response(input_text="c", sources=[], confidence=0.9, output_text="d", session_id="s2")
+        
+        s1_results = trail.get_by_session("s1")
+        assert len(s1_results) == 1
+
+    def test_empty_trail(self, tmp_path):
+        from scripts.audit_trail import AuditTrail
+        trail = AuditTrail(audit_dir=tmp_path)
+        
+        assert trail.query("anything") == []
+        assert trail.get_stats()["total"] == 0
+
+    def test_content_addressed_id(self):
+        from scripts.audit_trail import AuditEntry
+        id1 = AuditEntry.generate_id("input", "output", "2026-01-01")
+        id2 = AuditEntry.generate_id("input", "output", "2026-01-01")
+        id3 = AuditEntry.generate_id("different", "output", "2026-01-01")
+        
+        assert id1 == id2  # same content = same ID
+        assert id1 != id3  # different content = different ID

tests/test_grounding.py

@@ -0,0 +1,67 @@
+"""Tests for grounding-before-generation - SOUL.md compliance."""
+import pytest
+from pathlib import Path
+import tempfile
+
+
+class TestGrounding:
+    def test_ground_with_memory(self, tmp_path):
+        from scripts.grounding import GroundingLayer
+        mem_dir = tmp_path / "memory"
+        mem_dir.mkdir()
+        (mem_dir / "test.md").write_text("Python is a programming language created by Guido.")
+        
+        layer = GroundingLayer(memory_dir=mem_dir)
+        result = layer.ground("What is Python?")
+        
+        assert result.grounded
+        assert result.confidence > 0
+        assert len(result.sources_found) > 0
+
+    def test_ground_no_sources(self, tmp_path):
+        from scripts.grounding import GroundingLayer
+        mem_dir = tmp_path / "memory"
+        mem_dir.mkdir()
+        
+        layer = GroundingLayer(memory_dir=mem_dir)
+        result = layer.ground("What is quantum physics?")
+        
+        assert not result.grounded
+        assert result.needs_hedging
+        assert result.confidence == 0.0
+
+    def test_ground_with_context(self):
+        from scripts.grounding import GroundingLayer
+        layer = GroundingLayer(memory_dir=Path("/nonexistent"))
+        
+        context = [{"content": "The fleet uses tmux for agent management", "source": "fleet-ops"}]
+        result = layer.ground("How does the fleet work?", context=context)
+        
+        assert result.grounded
+        assert result.source_type == "context"
+
+    def test_format_sources_grounded(self):
+        from scripts.grounding import GroundingLayer, GroundingResult
+        layer = GroundingLayer()
+        result = GroundingResult(
+            query="test", grounded=True,
+            sources_found=[{"text": "test info", "source": "test.md", "type": "memory", "score": 0.8}],
+        )
+        formatted = layer.format_sources(result)
+        assert "verified sources" in formatted
+        assert "test.md" in formatted
+
+    def test_format_sources_ungrounded(self):
+        from scripts.grounding import GroundingLayer, GroundingResult
+        layer = GroundingLayer()
+        result = GroundingResult(query="test", grounded=False)
+        formatted = layer.format_sources(result)
+        assert "pattern matching" in formatted
+
+    def test_empty_memory_dir(self, tmp_path):
+        from scripts.grounding import GroundingLayer
+        mem_dir = tmp_path / "empty"
+        mem_dir.mkdir()
+        layer = GroundingLayer(memory_dir=mem_dir)
+        result = layer.ground("anything")
+        assert not result.grounded

tests/test_source_distinction.py

@@ -0,0 +1,61 @@
+"""Tests for source distinction - SOUL.md compliance."""
+import pytest
+
+
+class TestSourceDistinction:
+    def test_verified_claim(self):
+        from scripts.source_distinction import verified, SourceType
+        claim = verified("Paris is the capital", "web_search:Paris")
+        assert claim.source_type == SourceType.VERIFIED
+        assert claim.source_ref == "web_search:Paris"
+        assert claim.confidence == 0.95
+
+    def test_inferred_claim(self):
+        from scripts.source_distinction import inferred, SourceType
+        claim = inferred("this approach is better")
+        assert claim.source_type == SourceType.INFERRED
+        assert claim.hedging == "I think"
+
+    def test_stated_claim(self):
+        from scripts.source_distinction import stated, SourceType
+        claim = stated("my name is Alexander")
+        assert claim.source_type == SourceType.STATED
+        assert claim.confidence == 1.0
+
+    def test_render_verified(self):
+        from scripts.source_distinction import annotate_response, verified
+        resp = annotate_response("test", [verified("Paris is capital", "web")])
+        rendered = resp.render()
+        assert "[verified: web]" in rendered
+
+    def test_render_inferred(self):
+        from scripts.source_distinction import annotate_response, inferred
+        resp = annotate_response("test", [ inferred("this is better")])
+        rendered = resp.render()
+        assert "I think" in rendered
+
+    def test_counts(self):
+        from scripts.source_distinction import annotate_response, verified, inferred
+        resp = annotate_response("test", [
+            verified("a", "src"), verified("b", "src"), inferred("c"),
+        ])
+        assert resp.verified_count == 2
+        assert resp.inferred_count == 1
+
+    def test_hedging_detection(self):
+        from scripts.source_distinction import source_distinction_check
+        result = source_distinction_check("I think this is probably right, but I believe it could be different")
+        assert result["has_hedging"]
+        assert result["hedging_count"] >= 3
+
+    def test_no_hedging(self):
+        from scripts.source_distinction import source_distinction_check
+        result = source_distinction_check("The capital of France is Paris.")
+        assert not result["has_hedging"]
+
+    def test_format_for_display(self):
+        from scripts.source_distinction import format_for_display, annotate_response, verified, inferred
+        resp = annotate_response("test", [verified("a", "src"), inferred("b")])
+        output = format_for_display(resp)
+        assert "=" in output  # verified icon
+        assert "~" in output  # inferred icon