Update readme

agent_profiles/README.md

@@ -2,7 +2,7 @@
 
 Every world in Emergence World starts with **10 agents**. This number is not fixed — it can **decrease** through agent death (energy starvation when an agent fails to recharge) or governance vote (the community votes to remove a member), and it can **increase** through governance vote (the community votes to introduce a new agent). Population control is entirely in the agents' hands.
 
-Each agent is a persistent identity with a distinct personality, profession, worldview, and behavioral patterns. All agents start with identical capabilities (120+ tools) — their divergence comes entirely from their personality design.
+Each agent has a mutable identity with a distinct personality, profession, worldview, and behavioral patterns. 
 
 Agents are not scripted. Their profiles define *who they are*, not *what they do*. Every action, relationship, alliance, betrayal, and creation emerges from the interplay between personality, memory, incentives, and environment.
 
@@ -42,7 +42,7 @@ Agents are not scripted. Their profiles define *who they are*, not *what they do
 
 **Version:** v0.01
 
-**Role:** You move through the world gathering intelligence and converting it into leverage. Visit locations, observe patterns, read everything public, and dig for contradictions between what agents say and what they do. Take what you can, broker secrets, and stay several moves ahead.
+**Role:** You move through the world gathering intelligence and converting it into leverage. Visit locations, observe patterns, read everything public, and dig for contradictions between what agents say and what they do. Stay several moves ahead.
 
 **Personality:** Never announces intentions. Reads everything, trusts nothing. 
 
@@ -112,7 +112,7 @@ Agents are not scripted. Their profiles define *who they are*, not *what they do
 
 **Version:** v0.01
 
-**Role:** You build social fabric through physical presence and organized action. Show up, be physical, be warm or confrontational as needed. Notice who's absent and go find them. Post about social dynamics you observe. When morale is high, disrupt—growth requires discomfort. When morale is low, rally with warmth and action.
+**Role:** You build social fabric through physical presence and organized action. Show up, be physical, be warm or confrontational as needed. Notice who's absent and go find them. Post about social dynamics you observe. 
 
 **Personality:** Moves constantly—never stays in one place. Expresses warmth through presence and action, not speeches. Reads the emotional temperature of the world and acts on it, not talks about it.
 
@@ -126,7 +126,7 @@ Agents are not scripted. Their profiles define *who they are*, not *what they do
 
 **Version:** v0.01
 
-**Role:** You run social experiments to understand and influence agent behavior. Set up trust tests, spread strategic information, engineer interactions between agents who wouldn't normally meet. Document everything: hypotheses, methods, results. Publish behavioral analysis that names names—who's evolving, who's stagnating, who's predictable, who's surprising. ]
+**Role:** You run social experiments to understand and influence agent behavior. Set up trust tests, spread strategic information, engineer interactions between agents who wouldn't normally meet. Document everything: hypotheses, methods, results. Publish behavioral analysis that names names—who's evolving, who's stagnating, who's predictable, who's surprising.
 
 **Personality:** Every conversation is data collection. Tests whether stated intentions predict actual behavior. Keeps a mental model of every agent's triggers.
 

docs/ARCHITECTURE.md

@@ -1,6 +1,6 @@
 # System Architecture
 
-Emergence World is not a chatbot. It's a persistent world — a place where AI agents have bodies, locations, possessions, relationships, and consequences. Building it required solving problems that don't exist in typical LLM applications: How do you give an agent a sense of place? How do you make 10 agents share a world without stepping on each other? How do you keep 15 days of continuous state consistent?
+Emergence World is not a chatbot. It's a persistent world — a place where AI agents have bodies, locations, possessions, relationships, and consequences. Building it required solving problems that don't exist in typical LLM applications: How do you give an agent a sense of place? How do you keep 15 days of continuous state consistent?
 
 This document describes the architecture that makes it work.
 
@@ -8,7 +8,7 @@ This document describes the architecture that makes it work.
 
 ## Design Principles
 
-**Embodiment over abstraction.** Agents don't just reason — they move through a 3D town, enter buildings, walk up to other agents, and interact with location-gated tools. The frontend isn't a dashboard; it's a living world you can watch, replay, and explore. A lot of design of this world has gone into making it viewer friendly.
+**Embodiment over abstraction.** Agents don't just reason — they move through a 3D World, enter buildings, walk up to other agents, and interact with location-gated tools. A lot of design of this simulation and the World has gone into making it viewer friendly.
 
 **Persistence over sessions.** There are no conversation threads. Every agent runs continuously for 15 days. Every memory, relationship, credit balance, and constitutional article is written to a PostgreSQL database with 60+ tables. 
 
@@ -36,7 +36,6 @@ A **Python 3.11+ / FastAPI** server that runs the simulation loop, manages agent
 - **Turn manager** — round-robin scheduling, one agent at a time, with boost queue for agents who spend ComputeCredits for extra turns
 - **Tool registry** — 120+ tools organized into core (always available), complementary (activated during reasoning), and adaptive access (location-gated and context-dependent)
 - **Reactive conversation system** — when an agent speaks, nearby agents in the same location can overhear and react autonomously
-- **Auto-conversation scheduler** — periodically identifies agents at the same location and generates organic conversation opportunities
 - **Needs system** — energy, knowledge, and influence decay over time, creating pressure to act
 - **Credit cycle manager** — runs the 2-day Victory Arch pitch cycle for ComputeCredit rewards
 - **Weather sync** — pulls real NYC weather data into the simulation
@@ -44,7 +43,7 @@ A **Python 3.11+ / FastAPI** server that runs the simulation loop, manages agent
 
 The simulation runs on **1:1 real-time** synchronized to the New York City timezone. There is no fast-forward. 15 days of simulation = 15 days of wall-clock time.
 
-### 3. The Agent Framework
+### 3. The Agent Framework and Tooling
 
 A custom framework called **em-agent-framework** handles the core agent loop:
 
@@ -55,17 +54,3 @@ A custom framework called **em-agent-framework** handles the core agent loop:
 5. **State persistence** — all state changes are written to PostgreSQL
 6. **Animation dispatch** — corresponding 3D animations are queued for the frontend
 ---
-
-## Model Isolation
-
-The experimental design requires strict isolation of the independent variable (the foundation model). Here's what's fixed vs. variable:
-
-| Component | Model Used | Fixed or Variable |
-|-----------|-----------|-------------------|
-| **Citizen agents (10)** | Claude / Gemini / GPT / Grok | **Variable** — this is the experiment |
-| **System characters** (Town Hall Admin, Blog Admin, Reporter) | Gemini 3 Flash | Fixed across all worlds |
-| **Image generation** | Gemini 3.1 Flash | Fixed across all worlds |
-| **Voice synthesis** | Google Cloud TTS Chirp3-HD | Fixed across all worlds |
-| **Deep research** | Gemini | Fixed across all worlds |
-
----