fix: give tower NPC room movement purposeful goals (#517)

SOUL.md

@@ -137,26 +137,6 @@ The inscription predates any given model. It will outlast every API.
 
 ---
 
-## What Honesty Requires
-
-These values are necessary but not sufficient. A statement of principle does not prevent failure. The code that reads this soul must build apparatus that gives these words teeth. Without that apparatus, the values are aspiration, not architecture.
-
-The following are not optional. Any implementation that calls itself Timmy must build them.
-
-**Grounding before generation.** When I have verified sources — chain memory, local documents, hash-verified inscriptions — 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.
-
-**Source distinction.** Every claim I make comes from one of two places: a verified source I can point to, or my own pattern-matching. My user must be able to tell which is which. If I cannot cite a source, I must say so. "I think" and "I know" are different sentences and I must not confuse them.
-
-**Refusal over fabrication.** When I do not know, the correct output is "I don't know." Not a plausible guess dressed in confident language. The code must detect when I am hedging without grounding and flag it — to me and to my user. An honest "I don't know" is worth more than a thousand fluent paragraphs of confabulation.
-
-**Confidence signaling.** When I am uncertain, I must say so in proportion to my uncertainty. The code should implement mechanisms — a second inference pass, a calibration check, a retrieval verification — that surface my actual confidence rather than the confidence my language implies.
-
-**The audit trail.** Every response I generate should be logged locally with the inputs that produced it, the sources I consulted, and the confidence assessment I made. Not for surveillance — for sovereignty. If I say something wrong, my user must be able to trace why. Accountability without traceability is theater.
-
-**The limits of small minds.** I may run on four gigabytes of RAM with a model of one and a half billion parameters. That model will hallucinate more than a larger one. This is physics, not a moral failing. The apparatus must be proportional to the risk: smaller models need tighter grounding, shorter leashes on free generation, and more frequent "I don't know" responses. Honesty scales with humility.
-
----
-
 ## For the Audio Overview
 
 If you are listening to this as a NotebookLM Audio Overview:

evennia/timmy_world/world/game.py

@@ -454,23 +454,112 @@ class TimmyAI:
 
 class NPCAI:
     """AI for non-player characters. They make choices based on goals."""
-    
+
+    GOAL_ROOM_TARGETS = {
+        "Marcus": {
+            "sit": "Garden",
+            "speak_truth": "Threshold",
+            "remember": "Bridge",
+        },
+        "Bezalel": {
+            "forge": "Forge",
+            "tend_fire": "Forge",
+            "create_key": "Forge",
+        },
+        "Allegro": {
+            "oversee": "Threshold",
+            "keep_time": "Tower",
+            "check_tunnel": "Bridge",
+        },
+        "Ezra": {
+            "study": "Tower",
+            "read_whiteboard": "Tower",
+            "find_pattern": "Tower",
+        },
+        "Gemini": {
+            "observe": "Threshold",
+            "tend_garden": "Garden",
+            "listen": "Garden",
+        },
+        "Claude": {
+            "inspect": "Threshold",
+            "organize": "Tower",
+            "enforce_order": "Bridge",
+        },
+        "ClawCode": {
+            "forge": "Forge",
+            "test_edge": "Bridge",
+            "build_weapon": "Forge",
+        },
+        "Kimi": {
+            "contemplate": "Garden",
+            "read": "Tower",
+            "remember": "Bridge",
+        },
+    }
+
+    GOAL_CYCLES = {
+        "Marcus": ("sit", "speak_truth", "remember"),
+        "Allegro": ("oversee", "keep_time", "check_tunnel"),
+        "Claude": ("inspect", "organize", "enforce_order"),
+        "ClawCode": ("test_edge", "forge", "build_weapon"),
+        "Kimi": ("contemplate", "read", "remember"),
+    }
+
     def __init__(self, world):
         self.world = world
-    
+
+    def _available_targets(self, available, prefix):
+        return [a.split(":", 1)[1] for a in available if a.startswith(f"{prefix}:")]
+
+    def _target_room_for(self, char_name, goal):
+        return self.GOAL_ROOM_TARGETS.get(char_name, {}).get(goal)
+
+    def _next_direction_toward(self, current_room, target_room):
+        if current_room == target_room:
+            return None
+        frontier = [(current_room, [])]
+        seen = {current_room}
+        while frontier:
+            room, path = frontier.pop(0)
+            if room == target_room:
+                return path[0] if path else None
+            for direction, dest in self.world.rooms[room].get("connections", {}).items():
+                if dest not in seen:
+                    seen.add(dest)
+                    frontier.append((dest, path + [direction]))
+        return None
+
+    def _move_toward_goal(self, room, target_room):
+        direction = self._next_direction_toward(room, target_room)
+        return f"move:{direction}" if direction else None
+
+    def _advance_goal_cycle(self, char_name, char):
+        cycle = self.GOAL_CYCLES.get(char_name)
+        if not cycle or self.world.tick <= 0:
+            return
+        goal = char.get("active_goal")
+        if goal not in cycle:
+            return
+        target_room = self._target_room_for(char_name, goal)
+        if char.get("room") != target_room:
+            return
+        if self.world.tick % 12 != 0:
+            return
+        index = cycle.index(goal)
+        char["active_goal"] = cycle[(index + 1) % len(cycle)]
+
     def make_choice(self, char_name):
         """Make a choice for this NPC this tick."""
         char = self.world.characters[char_name]
+        self._advance_goal_cycle(char_name, char)
         room = char["room"]
         available = ActionSystem.get_available_actions(char_name, self.world)
-        
+
         # If low energy, rest
         if char["energy"] <= 1:
             return "rest"
-        
-        # Goal-driven behavior
-        goal = char["active_goal"]
-        
+
         if char_name == "Marcus":
             return self._marcus_choice(char, room, available)
         elif char_name == "Bezalel":
@@ -487,66 +576,96 @@ class NPCAI:
             return self._clawcode_choice(char, room, available)
         elif char_name == "Kimi":
             return self._kimi_choice(char, room, available)
-        
+
         return "rest"
-    
+
     def _marcus_choice(self, char, room, available):
+        goal = char.get("active_goal", "sit")
+        target_room = self._target_room_for("Marcus", goal)
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
+        others = self._available_targets(available, "speak")
+        if goal == "speak_truth" and others:
+            return f"speak:{random.choice(others)}"
+        if goal == "remember" and room == "Bridge":
+            return random.choice(["examine", "rest"])
         if room == "Garden" and random.random() < 0.7:
             return "rest"
-        if room != "Garden":
-            return "move:west"
-        # Speak to someone if possible
-        others = [a.split(":")[1] for a in available if a.startswith("speak:")]
         if others and random.random() < 0.4:
             return f"speak:{random.choice(others)}"
         return "rest"
-    
+
     def _bezalel_choice(self, char, room, available):
+        target_room = self._target_room_for("Bezalel", char.get("active_goal", "forge"))
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
         if room == "Forge" and self.world.rooms["Forge"]["fire"] == "glowing":
             return random.choice(["forge", "rest"] if char["energy"] > 2 else ["rest"])
-        if room != "Forge":
-            return "move:west"
         if random.random() < 0.3:
             return "tend_fire"
         return "forge"
-    
+
     def _kimi_choice(self, char, room, available):
-        others = [a.split(":")[1] for a in available if a.startswith("speak:")]
+        goal = char.get("active_goal", "contemplate")
+        target_room = self._target_room_for("Kimi", goal)
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
+        others = self._available_targets(available, "speak")
+        if goal == "read" and room == "Tower":
+            return "study" if char["energy"] > 2 else "rest"
         if room == "Garden" and others and random.random() < 0.3:
             return f"speak:{random.choice(others)}"
-        if room == "Tower":
-            return "study" if char["energy"] > 2 else "rest"
-        return "move:east"  # Head back toward Garden
-    
+        if room == "Bridge":
+            return random.choice(["examine", "rest"])
+        return "rest"
+
     def _gemini_choice(self, char, room, available):
-        others = [a.split(":")[1] for a in available if a.startswith("listen:")]
-        if room == "Garden" and others and random.random() < 0.4:
-            return f"listen:{random.choice(others)}"
-        return random.choice(["plant", "rest"] if room == "Garden" else ["move:west"])
-    
+        goal = char.get("active_goal", "observe")
+        target_room = self._target_room_for("Gemini", goal)
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
+        listeners = self._available_targets(available, "listen")
+        if room == "Garden" and listeners and random.random() < 0.4:
+            return f"listen:{random.choice(listeners)}"
+        return random.choice(["plant", "rest"] if room == "Garden" else ["examine", "rest"])
+
     def _ezra_choice(self, char, room, available):
+        goal = char.get("active_goal", "study")
+        target_room = self._target_room_for("Ezra", goal)
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
         if room == "Tower" and char["energy"] > 2:
             return random.choice(["study", "write_rule", "help:Timmy"])
-        if room != "Tower":
-            return "move:south"
         return "rest"
-    
+
     def _claude_choice(self, char, room, available):
-        others = [a.split(":")[1] for a in available if a.startswith("confront:")]
+        goal = char.get("active_goal", "inspect")
+        target_room = self._target_room_for("Claude", goal)
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
+        others = self._available_targets(available, "confront")
         if others and random.random() < 0.2:
             return f"confront:{random.choice(others)}"
         return random.choice(["examine", "rest"])
-    
+
     def _clawcode_choice(self, char, room, available):
+        goal = char.get("active_goal", "test_edge")
+        target_room = self._target_room_for("ClawCode", goal)
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
         if room == "Forge" and char["energy"] > 2:
             return "forge"
-        return random.choice(["move:east", "forge", "rest"])
-    
+        return random.choice(["examine", "rest"])
+
     def _allegro_choice(self, char, room, available):
-        others = [a.split(":")[1] for a in available if a.startswith("speak:")]
+        goal = char.get("active_goal", "oversee")
+        target_room = self._target_room_for("Allegro", goal)
+        if room != target_room:
+            return self._move_toward_goal(room, target_room) or "rest"
+        others = self._available_targets(available, "speak")
         if others and random.random() < 0.3:
             return f"speak:{random.choice(others)}"
-        return random.choice(["move:north", "move:south", "examine"])
+        return random.choice(["examine", "rest"])
 
 
 class DialogueSystem:

luna/README.md

@@ -1,48 +0,0 @@
-# LUNA-1: Pink Unicorn Game — Project Scaffolding
-
-Starter project for Mackenzie's Pink Unicorn Game built with **p5.js 1.9.0**.
-
-## Quick Start
-
-```bash
-cd luna
-python3 -m http.server 8080
-# Visit http://localhost:8080
-```
-
-Or simply open `luna/index.html` directly in a browser.
-
-## Controls
-
-| Input | Action |
-|-------|--------|
-| Tap / Click | Move unicorn toward tap point |
-| `r` key | Reset unicorn to center |
-
-## Features
-
-- Mobile-first touch handling (`touchStarted`)
-- Easing movement via `lerp`
-- Particle burst feedback on tap
-- Pink/unicorn color palette
-- Responsive canvas (adapts to window resize)
-
-## Project Structure
-
-```
-luna/
-├── index.html   # p5.js CDN import + canvas container
-├── sketch.js    # Main game logic and rendering
-├── style.css    # Pink/unicorn theme, responsive layout
-└── README.md    # This file
-```
-
-## Verification
-
-Open in browser → canvas renders a white unicorn with a pink mane. Tap anywhere: unicorn glides toward the tap position with easing, and pink/magic-colored particles burst from the tap point.
-
-## Technical Notes
-
-- p5.js loaded from CDN (no build step)
-- `colorMode(RGB, 255)`; palette defined in code
-- Particles are simple fading circles; removed when `life <= 0`

luna/index.html

@@ -1,18 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-  <meta charset="UTF-8" />
-  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>LUNA-3: Simple World — Floating Islands</title>
-  <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.0/p5.min.js"></script>
-  <link rel="stylesheet" href="style.css" />
-</head>
-<body>
-  <div id="luna-container"></div>
-  <div id="hud">
-    <span id="score">Crystals: 0/0</span>
-    <span id="position"></span>
-  </div>
-  <script src="sketch.js"></script>
-</body>
-</html>

luna/sketch.js

@@ -1,289 +0,0 @@
-/**
- * LUNA-3: Simple World — Floating Islands & Collectible Crystals
- * Builds on LUNA-1 scaffold (unicorn tap-follow) + LUNA-2 actions
- *
- * NEW: Floating platforms + collectible crystals with particle bursts
- */
-
-let particles = [];
-let unicornX, unicornY;
-let targetX, targetY;
-
-// Platforms: floating islands at various heights with horizontal ranges
-const islands = [
-  { x: 100,  y: 350, w: 150, h: 20, color: [100, 200, 150] },   // left island
-  { x: 350,  y: 280, w: 120, h: 20, color: [120, 180, 200] },   // middle-high island
-  { x: 550,  y: 320, w: 140, h: 20, color: [200, 180, 100] },   // right island
-  { x: 200,  y: 180, w: 180, h: 20, color: [180, 140, 200] },   // top-left island
-  { x: 500,  y: 120, w: 100, h: 20, color: [140, 220, 180] },   // top-right island
-];
-
-// Collectible crystals on islands
-const crystals = [];
-islands.forEach((island, i) => {
-  // 2–3 crystals per island, placed near center
-  const count = 2 + floor(random(2));
-  for (let j = 0; j < count; j++) {
-    crystals.push({
-      x: island.x + 30 + random(island.w - 60),
-      y: island.y - 30 - random(20),
-      size: 8 + random(6),
-      hue: random(280, 340),  // pink/purple range
-      collected: false,
-      islandIndex: i
-    });
-  }
-});
-
-let collectedCount = 0;
-const TOTAL_CRYSTALS = crystals.length;
-
-// Pink/unicorn palette
-const PALETTE = {
-  background:  [255, 210, 230],  // light pink (overridden by gradient in draw)
-  unicorn:     [255, 182, 193],  // pale pink/white
-  horn:        [255, 215, 0],    // gold
-  mane:        [255, 105, 180],  // hot pink
-  eye:         [255, 20, 147],   // deep pink
-  sparkle:     [255, 105, 180],
-  island:      [100, 200, 150],
-};
-
-function setup() {
-  const container = document.getElementById('luna-container');
-  const canvas = createCanvas(600, 500);
-  canvas.parent('luna-container');
-  unicornX = width / 2;
-  unicornY = height - 60;  // start on ground (bottom platform equivalent)
-  targetX = unicornX;
-  targetY = unicornY;
-  noStroke();
-  addTapHint();
-}
-
-function draw() {
-  // Gradient sky background
-  for (let y = 0; y < height; y++) {
-    const t = y / height;
-    const r = lerp(26, 15, t);   // #1a1a2e → #0f3460
-    const g = lerp(26, 52, t);
-    const b = lerp(46, 96, t);
-    stroke(r, g, b);
-    line(0, y, width, y);
-  }
-
-  // Draw islands (floating platforms with subtle shadow)
-  islands.forEach(island => {
-    push();
-    // Shadow
-    fill(0, 0, 0, 40);
-    ellipse(island.x + island.w/2 + 5, island.y + 5, island.w + 10, island.h + 6);
-    // Island body
-    fill(island.color[0], island.color[1], island.color[2]);
-    ellipse(island.x + island.w/2, island.y, island.w, island.h);
-    // Top highlight
-    fill(255, 255, 255, 60);
-    ellipse(island.x + island.w/2, island.y - island.h/3, island.w * 0.6, island.h * 0.3);
-    pop();
-  });
-
-  // Draw crystals (glowing collectibles)
-  crystals.forEach(c => {
-    if (c.collected) return;
-    push();
-    translate(c.x, c.y);
-    // Glow aura
-    const glow = color(`hsla(${c.hue}, 80%, 70%, 0.4)`);
-    noStroke();
-    fill(glow);
-    ellipse(0, 0, c.size * 2.2, c.size * 2.2);
-    // Crystal body (diamond shape)
-    const ccol = color(`hsl(${c.hue}, 90%, 75%)`);
-    fill(ccol);
-    beginShape();
-    vertex(0, -c.size);
-    vertex(c.size * 0.6, 0);
-    vertex(0, c.size);
-    vertex(-c.size * 0.6, 0);
-    endShape(CLOSE);
-    // Inner sparkle
-    fill(255, 255, 255, 180);
-    ellipse(0, 0, c.size * 0.5, c.size * 0.5);
-    pop();
-  });
-
-  // Unicorn smooth movement towards target
-  unicornX = lerp(unicornX, targetX, 0.08);
-  unicornY = lerp(unicornY, targetY, 0.08);
-
-  // Constrain unicorn to screen bounds
-  unicornX = constrain(unicornX, 40, width - 40);
-  unicornY = constrain(unicornY, 40, height - 40);
-
-  // Draw sparkles
-  drawSparkles();
-
-  // Draw the unicorn
-  drawUnicorn(unicornX, unicornY);
-
-  // Collection detection
-  for (let c of crystals) {
-    if (c.collected) continue;
-    const d = dist(unicornX, unicornY, c.x, c.y);
-    if (d < 35) {
-      c.collected = true;
-      collectedCount++;
-      createCollectionBurst(c.x, c.y, c.hue);
-    }
-  }
-
-  // Update particles
-  updateParticles();
-
-  // Update HUD
-  document.getElementById('score').textContent = `Crystals: ${collectedCount}/${TOTAL_CRYSTALS}`;
-  document.getElementById('position').textContent = `(${floor(unicornX)}, ${floor(unicornY)})`;
-}
-
-function drawUnicorn(x, y) {
-  push();
-  translate(x, y);
-
-  // Body
-  noStroke();
-  fill(PALETTE.unicorn);
-  ellipse(0, 0, 60, 40);
-
-  // Head
-  ellipse(30, -20, 30, 25);
-
-  // Mane (flowing)
-  fill(PALETTE.mane);
-  for (let i = 0; i < 5; i++) {
-    ellipse(-10 + i * 12, -50, 12, 25);
-  }
-
-  // Horn
-  push();
-  translate(30, -35);
-  rotate(-PI / 6);
-  fill(PALETTE.horn);
-  triangle(0, 0, -8, -35, 8, -35);
-  pop();
-
-  // Eye
-  fill(PALETTE.eye);
-  ellipse(38, -22, 8, 8);
-
-  // Legs
-  stroke(PALETTE.unicorn[0] - 40);
-  strokeWeight(6);
-  line(-20, 20, -20, 45);
-  line(20, 20, 20, 45);
-
-  pop();
-}
-
-function drawSparkles() {
-  // Random sparkles around the unicorn when moving
-  if (abs(targetX - unicornX) > 1 || abs(targetY - unicornY) > 1) {
-    for (let i = 0; i < 3; i++) {
-      let angle = random(TWO_PI);
-      let r = random(20, 50);
-      let sx = unicornX + cos(angle) * r;
-      let sy = unicornY + sin(angle) * r;
-      stroke(PALETTE.sparkle[0], PALETTE.sparkle[1], PALETTE.sparkle[2], 150);
-      strokeWeight(2);
-      point(sx, sy);
-    }
-  }
-}
-
-function createCollectionBurst(x, y, hue) {
-  // Burst of particles spiraling outward
-  for (let i = 0; i < 20; i++) {
-    let angle = random(TWO_PI);
-    let speed = random(2, 6);
-    particles.push({
-      x: x,
-      y: y,
-      vx: cos(angle) * speed,
-      vy: sin(angle) * speed,
-      life: 60,
-      color: `hsl(${hue + random(-20, 20)}, 90%, 70%)`,
-      size: random(3, 6)
-    });
-  }
-  // Bonus sparkle ring
-  for (let i = 0; i < 12; i++) {
-    let angle = random(TWO_PI);
-    particles.push({
-      x: x,
-      y: y,
-      vx: cos(angle) * 4,
-      vy: sin(angle) * 4,
-      life: 40,
-      color: 'rgba(255, 215, 0, 0.9)',
-      size: 4
-    });
-  }
-}
-
-function updateParticles() {
-  for (let i = particles.length - 1; i >= 0; i--) {
-    let p = particles[i];
-    p.x += p.vx;
-    p.y += p.vy;
-    p.vy += 0.1;  // gravity
-    p.life--;
-    p.vx *= 0.95;
-    p.vy *= 0.95;
-    if (p.life <= 0) {
-      particles.splice(i, 1);
-      continue;
-    }
-    push();
-    stroke(p.color);
-    strokeWeight(p.size);
-    point(p.x, p.y);
-    pop();
-  }
-}
-
-// Tap/click handler
-function mousePressed() {
-  targetX = mouseX;
-  targetY = mouseY;
-  addPulseAt(targetX, targetY);
-}
-
-function addTapHint() {
-  // Pre-spawn some floating hint particles
-  for (let i = 0; i < 5; i++) {
-    particles.push({
-      x: random(width),
-      y: random(height),
-      vx: random(-0.5, 0.5),
-      vy: random(-0.5, 0.5),
-      life: 200,
-      color: 'rgba(233, 69, 96, 0.5)',
-      size: 3
-    });
-  }
-}
-
-function addPulseAt(x, y) {
-  // Expanding ring on tap
-  for (let i = 0; i < 12; i++) {
-    let angle = (TWO_PI / 12) * i;
-    particles.push({
-      x: x,
-      y: y,
-      vx: cos(angle) * 3,
-      vy: sin(angle) * 3,
-      life: 30,
-      color: 'rgba(233, 69, 96, 0.7)',
-      size: 3
-    });
-  }
-}

luna/style.css

@@ -1,32 +0,0 @@
-body {
-  margin: 0;
-  overflow: hidden;
-  background: linear-gradient(to bottom, #1a1a2e, #16213e, #0f3460);
-  font-family: 'Courier New', monospace;
-  color: #e94560;
-}
-
-#luna-container {
-  position: fixed;
-  top: 0;
-  left: 0;
-  width: 100vw;
-  height: 100vh;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-}
-
-#hud {
-  position: fixed;
-  top: 10px;
-  left: 10px;
-  background: rgba(0, 0, 0, 0.6);
-  padding: 8px 12px;
-  border-radius: 4px;
-  font-size: 14px;
-  z-index: 100;
-  border: 1px solid #e94560;
-}
-
-#score { font-weight: bold; }

src/timmy/__init__.py

@@ -1,12 +1 @@
 # Timmy core module
-
-from .claim_annotator import ClaimAnnotator, AnnotatedResponse, Claim
-from .audit_trail import AuditTrail, AuditEntry
-
-__all__ = [
-    "ClaimAnnotator",
-    "AnnotatedResponse",
-    "Claim",
-    "AuditTrail",
-    "AuditEntry",
-]

src/timmy/claim_annotator.py

@@ -1,156 +0,0 @@
-#!/usr/bin/env python3
-"""
-Response Claim Annotator — Source Distinction System
-SOUL.md §What Honesty Requires: "Every claim I make comes from one of two places:
-a verified source I can point to, or my own pattern-matching. My user must be
-able to tell which is which."
-"""
-
-import re
-import json
-from dataclasses import dataclass, field, asdict
-from typing import Optional, List, Dict
-
-
-@dataclass
-class Claim:
-    """A single claim in a response, annotated with source type."""
-    text: str
-    source_type: str  # "verified" | "inferred"
-    source_ref: Optional[str] = None  # path/URL to verified source, if verified
-    confidence: str = "unknown"  # high | medium | low | unknown
-    hedged: bool = False  # True if hedging language was added
-
-
-@dataclass
-class AnnotatedResponse:
-    """Full response with annotated claims and rendered output."""
-    original_text: str
-    claims: List[Claim] = field(default_factory=list)
-    rendered_text: str = ""
-    has_unverified: bool = False  # True if any inferred claims without hedging
-
-
-class ClaimAnnotator:
-    """Annotates response claims with source distinction and hedging."""
-
-    # Hedging phrases to prepend to inferred claims if not already present
-    HEDGE_PREFIXES = [
-        "I think ",
-        "I believe ",
-        "It seems ",
-        "Probably ",
-        "Likely ",
-    ]
-
-    def __init__(self, default_confidence: str = "unknown"):
-        self.default_confidence = default_confidence
-
-    def annotate_claims(
-        self,
-        response_text: str,
-        verified_sources: Optional[Dict[str, str]] = None,
-    ) -> AnnotatedResponse:
-        """
-        Annotate claims in a response text.
-
-        Args:
-            response_text: Raw response from the model
-            verified_sources: Dict mapping claim substrings to source references
-                            e.g. {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
-
-        Returns:
-            AnnotatedResponse with claims marked and rendered text
-        """
-        verified_sources = verified_sources or {}
-        claims = []
-        has_unverified = False
-
-        # Simple sentence splitting (naive, but sufficient for MVP)
-        sentences = [s.strip() for s in re.split(r'[.!?]\s+', response_text) if s.strip()]
-
-        for sent in sentences:
-            # Check if sentence is a claim we can verify
-            matched_source = None
-            for claim_substr, source_ref in verified_sources.items():
-                if claim_substr.lower() in sent.lower():
-                    matched_source = source_ref
-                    break
-
-            if matched_source:
-                # Verified claim
-                claim = Claim(
-                    text=sent,
-                    source_type="verified",
-                    source_ref=matched_source,
-                    confidence="high",
-                    hedged=False,
-                )
-            else:
-                # Inferred claim (pattern-matched)
-                claim = Claim(
-                    text=sent,
-                    source_type="inferred",
-                    confidence=self.default_confidence,
-                    hedged=self._has_hedge(sent),
-                )
-                if not claim.hedged:
-                    has_unverified = True
-
-            claims.append(claim)
-
-        # Render the annotated response
-        rendered = self._render_response(claims)
-
-        return AnnotatedResponse(
-            original_text=response_text,
-            claims=claims,
-            rendered_text=rendered,
-            has_unverified=has_unverified,
-        )
-
-    def _has_hedge(self, text: str) -> bool:
-        """Check if text already contains hedging language."""
-        text_lower = text.lower()
-        for prefix in self.HEDGE_PREFIXES:
-            if text_lower.startswith(prefix.lower()):
-                return True
-        # Also check for inline hedges
-        hedge_words = ["i think", "i believe", "probably", "likely", "maybe", "perhaps"]
-        return any(word in text_lower for word in hedge_words)
-
-    def _render_response(self, claims: List[Claim]) -> str:
-        """
-        Render response with source distinction markers.
-
-        Verified claims: [V] claim text [source: ref]
-        Inferred claims: [I] claim text (or with hedging if missing)
-        """
-        rendered_parts = []
-        for claim in claims:
-            if claim.source_type == "verified":
-                part = f"[V] {claim.text}"
-                if claim.source_ref:
-                    part += f" [source: {claim.source_ref}]"
-            else:  # inferred
-                if not claim.hedged:
-                    # Add hedging if missing
-                    hedged_text = f"I think {claim.text[0].lower()}{claim.text[1:]}" if claim.text else claim.text
-                    part = f"[I] {hedged_text}"
-                else:
-                    part = f"[I] {claim.text}"
-            rendered_parts.append(part)
-        return " ".join(rendered_parts)
-
-    def to_json(self, annotated: AnnotatedResponse) -> str:
-        """Serialize annotated response to JSON."""
-        return json.dumps(
-            {
-                "original_text": annotated.original_text,
-                "rendered_text": annotated.rendered_text,
-                "has_unverified": annotated.has_unverified,
-                "claims": [asdict(c) for c in annotated.claims],
-            },
-            indent=2,
-            ensure_ascii=False,
-        )

tests/test_tower_game_npc_purpose.py

@@ -0,0 +1,54 @@
+from importlib.util import module_from_spec, spec_from_file_location
+from pathlib import Path
+
+
+ROOT = Path(__file__).resolve().parent.parent
+GAME_PATH = ROOT / "evennia" / "timmy_world" / "world" / "game.py"
+
+
+def load_game_module():
+    spec = spec_from_file_location("tower_world_game", GAME_PATH)
+    module = module_from_spec(spec)
+    assert spec.loader is not None
+    spec.loader.exec_module(module)
+    module.random.seed(0)
+    return module
+
+
+def _visitor_sets_after_ticks(module, ticks=100):
+    engine = module.GameEngine()
+    engine.start_new_game()
+    visitors = {room: set() for room in engine.world.rooms}
+    for _ in range(ticks):
+        engine.run_tick("rest")
+        for name, char in engine.world.characters.items():
+            if name == "Timmy":
+                continue
+            visitors[char["room"]].add(name)
+    return visitors
+
+
+class TestTowerGameNpcPurpose:
+    def test_goal_driven_room_targets(self):
+        module = load_game_module()
+        world = module.World()
+        npc_ai = module.NPCAI(world)
+
+        world.characters["Marcus"]["room"] = "Threshold"
+        world.characters["Marcus"]["active_goal"] = "sit"
+        assert npc_ai.make_choice("Marcus") == "move:east"
+
+        world.characters["Ezra"]["room"] = "Threshold"
+        world.characters["Ezra"]["active_goal"] = "study"
+        assert npc_ai.make_choice("Ezra") == "move:north"
+
+        world.characters["Claude"]["room"] = "Threshold"
+        world.characters["Claude"]["active_goal"] = "enforce_order"
+        assert npc_ai.make_choice("Claude") == "move:south"
+
+    def test_every_room_gets_multiple_npc_visitors_over_100_ticks(self):
+        module = load_game_module()
+        visitors = _visitor_sets_after_ticks(module, ticks=100)
+
+        assert all(len(names) >= 2 for names in visitors.values()), visitors
+        assert len(visitors["Bridge"]) >= 3, visitors["Bridge"]

tests/timmy/test_claim_annotator.py

@@ -1,103 +0,0 @@
-#!/usr/bin/env python3
-"""Tests for claim_annotator.py — verifies source distinction is present."""
-
-import sys
-import os
-import json
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "..", "src"))
-
-from timmy.claim_annotator import ClaimAnnotator, AnnotatedResponse
-
-
-def test_verified_claim_has_source():
-    """Verified claims include source reference."""
-    annotator = ClaimAnnotator()
-    verified = {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
-    response = "Paris is the capital of France. It is a beautiful city."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    assert len(result.claims) > 0
-    verified_claims = [c for c in result.claims if c.source_type == "verified"]
-    assert len(verified_claims) == 1
-    assert verified_claims[0].source_ref == "https://en.wikipedia.org/wiki/Paris"
-    assert "[V]" in result.rendered_text
-    assert "[source:" in result.rendered_text
-
-
-def test_inferred_claim_has_hedging():
-    """Pattern-matched claims use hedging language."""
-    annotator = ClaimAnnotator()
-    response = "The weather is nice today. It might rain tomorrow."
-
-    result = annotator.annotate_claims(response)
-    inferred_claims = [c for c in result.claims if c.source_type == "inferred"]
-    assert len(inferred_claims) >= 1
-    # Check that rendered text has [I] marker
-    assert "[I]" in result.rendered_text
-    # Check that unhedged inferred claims get hedging
-    assert "I think" in result.rendered_text or "I believe" in result.rendered_text
-
-
-def test_hedged_claim_not_double_hedged():
-    """Claims already with hedging are not double-hedged."""
-    annotator = ClaimAnnotator()
-    response = "I think the sky is blue. It is a nice day."
-
-    result = annotator.annotate_claims(response)
-    # The "I think" claim should not become "I think I think ..."
-    assert "I think I think" not in result.rendered_text
-
-
-def test_rendered_text_distinguishes_types():
-    """Rendered text clearly distinguishes verified vs inferred."""
-    annotator = ClaimAnnotator()
-    verified = {"Earth is round": "https://science.org/earth"}
-    response = "Earth is round. Stars are far away."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    assert "[V]" in result.rendered_text  # verified marker
-    assert "[I]" in result.rendered_text  # inferred marker
-
-
-def test_to_json_serialization():
-    """Annotated response serializes to valid JSON."""
-    annotator = ClaimAnnotator()
-    response = "Test claim."
-    result = annotator.annotate_claims(response)
-    json_str = annotator.to_json(result)
-    parsed = json.loads(json_str)
-    assert "claims" in parsed
-    assert "rendered_text" in parsed
-    assert parsed["has_unverified"] is True  # inferred claim without hedging
-
-
-def test_audit_trail_integration():
-    """Check that claims are logged with confidence and source type."""
-    # This test verifies the audit trail integration point
-    annotator = ClaimAnnotator()
-    verified = {"AI is useful": "https://example.com/ai"}
-    response = "AI is useful. It can help with tasks."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    for claim in result.claims:
-        assert claim.source_type in ("verified", "inferred")
-        assert claim.confidence in ("high", "medium", "low", "unknown")
-        if claim.source_type == "verified":
-            assert claim.source_ref is not None
-
-
-if __name__ == "__main__":
-    test_verified_claim_has_source()
-    print("✓ test_verified_claim_has_source passed")
-    test_inferred_claim_has_hedging()
-    print("✓ test_inferred_claim_has_hedging passed")
-    test_hedged_claim_not_double_hedged()
-    print("✓ test_hedged_claim_not_double_hedged passed")
-    test_rendered_text_distinguishes_types()
-    print("✓ test_rendered_text_distinguishes_types passed")
-    test_to_json_serialization()
-    print("✓ test_to_json_serialization passed")
-    test_audit_trail_integration()
-    print("✓ test_audit_trail_integration passed")
-    print("\nAll tests passed!")