# Gamemodes Project Audit

**Audit Number:** 1
**Audit Date:** 2026-04-15
**Auditor:** Roo (AI Orchestrator)
**Prior Audit Date:** N/A (first audit)
**Repository Access:** Yes
**Revenue Status:** Pre-revenue / development stage

---

## PART 1 — TECHNICAL ASSET INVENTORY

### Codebase Scope

| Project | Python Files | LOC | Maturity |
|---------|-------------|-----|----------|
| Game Testing (Shadow City) | 174 | ~65,059 | Functional |
| Gamemodes01 | 13 | ~6,872 | Functional |
| Fallout 4 Mod | 18 | ~3,809 | Functional |
| Skyrim Mod | 19 + 6 C++ | ~2,649 + ~800 | Functional |
| Wendy | 4 | ~1,327 | Production-ready |
| scripts/ | ~30 | ~3,000 | Functional |
| bankai/ | ~12 | ~2,000 (est.) | Prototype |
| GMODE (crypto) | ~15 TS | ~2,000 (est.) | Prototype |
| **TOTAL** | **~259 Python + 6 C++** | **~79,716 + 800** | — |

### System Maturity Ratings

| System | Maturity |
|--------|----------|
| Gamemodes01 Training Pipeline | Functional (schemas complete, data generation active) |
| Game Testing World Engine | Functional (5 factions, tick system, 266 tests passing) |
| Game Testing Conversation Engine | Functional (LLM-driven dialogue, intent classification) |
| Fallout 4 NPC Dialogue Server | Functional (multi-backend LLM, 10,600 training records) |
| Skyrim SKSE Plugin | Functional (complete C++ plugin, not tested in-game) |
| Skyrim Dialogue Server | Functional (dual LLM provider, caching, prompt tiers) |
| Wendy Chat Demo | Production-ready (polished UI, 8-stage affinity) |
| Lydia 1B Models | Prototype (4 fine-tuning iterations, quality unvalidated) |

### Data Assets

- ~50,000+ psychology-labeled training records across all projects
- 4 fine-tuned Lydia 1B adapters (v1–v4) + GGUF exports
- Active data generation: 8,500/10,000 records (85% complete, ~57 min ETA)
- Training data pipeline with LLM judge (5-dimension scoring, auto-accept ≥4.5/5)

### Intellectual Property

- **Proprietary Psychology-Driven NPC Behavior System**: Novel application of psychology principles to NPC behavior
  - Behavioral progression design methodology → Behavioral patterns → Behavioral triggers → Core behavioral state
  - Affinity gating (0–100) controls which behavioral modules are accessible
  - Training data format includes behavioral context (active_module, affinity_level, trigger_topic)
- **Shadow City Game Design**: Noir text adventure, 5-faction system, tick-based simulation, time-travel mechanics
- **Multi-platform LLM architecture**: z.ai (GLM-5), LM Studio, OpenAI, Cerebras with failover
- **NPC schema system**: 9 JSON schemas, 7 physiological states × 3 behavioral modules × 20 archetypes × 8 genres

### Technical Debt

| Issue | Severity |
|-------|----------|
| Shadow City tick system: 5 critical bugs (`process_tick` never calls `_advance_clock`) | **High** |
| Training data imbalance: Firefighter 7,507 vs Manager 8 | Medium |
| Missing F4SE C++ plugin for Fallout 4 | Medium |
| Code duplication in Shadow City (context_builder, database, templates) | Medium |
| bankai and GMODE projects are early prototype stage | Low |

### External Dependencies

| Dependency | Risk |
|------------|------|
| z.ai API (GLM-5) | Medium — API costs, availability |
| LM Studio (local, deepseek-r1:8b) | Low — local |
| OpenAI API (optional) | Medium — paid |
| Cerebras API (free tier) | Low |

### Deployment Readiness

| Project | Ready? | Blockers |
|---------|--------|----------|
| Wendy | ✅ Yes | None |
| Skyrim Mod | ⚠️ Near | Needs in-game testing |
| Fallout 4 Mod | ⚠️ Partial | Missing C++ plugin |
| Game Testing | ❌ No | 5 critical tick bugs |
| Gamemodes01 | ❌ No | No trained model yet |

---

## PART 2 — REPLACEMENT COST VALUATION

Using 2025–2026 US freelance/contractor rates.

| Category | Estimated Hours | Rate ($/hr) | Low | Mid | High |
|----------|----------------|-------------|-----|-----|------|
| Python Backend (senior) | 800–1,200 | $75–150 | $60,000 | $105,000 | $180,000 |
| Game Design / Narrative | 400–600 | $50–100 | $20,000 | $40,000 | $60,000 |
| LLM/AI Engineering (fine-tuning, prompt engineering, psychology-driven NPC system) | 300–500 | $100–200 | $30,000 | $75,000 | $100,000 |
| C++ Plugin Development (SKSE) | 100–200 | $75–150 | $7,500 | $18,750 | $30,000 |
| Frontend / Web UI (Wendy, model_tester) | 100–200 | $60–120 | $6,000 | $15,000 | $24,000 |
| Training Data Generation (50K records) | 200–400 | $30–60 | $6,000 | $18,000 | $24,000 |
| QA / Testing | 150–300 | $40–80 | $6,000 | $18,000 | $24,000 |
| DevOps / Deployment (Docker, config, CI) | 80–160 | $60–120 | $4,800 | $12,000 | $19,200 |
| Documentation / Technical Writing | 100–200 | $50–80 | $5,000 | $12,500 | $16,000 |
| Fine-tuned Models (compute cost, 4 iterations) | — | — | $2,000 | $5,000 | $10,000 |
| **Total Replacement Cost** | | | **$147,300** | **$319,250** | **$487,200** |

### Discount Factor

Apply 20–30% discount for non-production-quality code in some subsystems (tick bugs, code duplication, prototype-stage bankai/GMODE).

**Discounted Replacement Cost:**

| Scenario | Discount | Value |
|----------|----------|-------|
| Low | 30% | **$103,110** |
| Mid | 25% | **$239,438** |
| High | 10% | **$438,480** |

---

## PART 3 — MARKET COMPARABLE ANALYSIS

| Comparable | Stage | Revenue / Valuation | Implied Shadow City Range |
|------------|-------|---------------------|---------------------------|
| AI Dungeon | Solo dev → seed | $15–25M (with 1.5M users) | $500K–$2M |
| NovelAI | Small team, early revenue | $1–3M ARR | $300K–$1.5M |
| AI Roguelite | Solo dev, Steam | $100K–$500K revenue | $200K–$800K |
| Convai | Small team, seed (VC) | $20–30M seed | $500K–$2M |
| Replika | Small team → scale | $5–15M (seed stage) | $300K–$1.5M |

**Composite Implied Range:**

| Scenario | Value | Rationale |
|----------|-------|-----------|
| Low | **$200K** | Indie Steam release, modest traction |
| Mid | **$500K–$1M** | B2B potential demonstrated |
| High | **$2M** | AI Dungeon-level traction or seed funding |

---

## PART 4 — FORWARD-LOOKING REVENUE POTENTIAL

### 4A. Revenue Model Candidates

| Model | Description | Feasibility |
|-------|-------------|-------------|
| Game Sales (Steam Early Access) | Sell Shadow City as standalone game | ✅ Proven (indie AI games on Steam exist) |
| B2B Psychology-Driven Dialogue Engine Licensing | License psychology-driven dialogue engine to game studios | ⚠️ Plausible (Convai/Inworld validate market) |
| Fine-tuned Model Licensing | Sell pre-trained psychology-informed dialogue models | ⚠️ Speculative (market unproven for 1B models) |
| API SaaS (Wendy-style) | Hosted NPC dialogue API with subscription | ⚠️ Plausible (Convai model) |
| Training Data Sales | Sell curated psychology-labeled dialogue datasets | ❌ Speculative (niche market) |

### 4B. Scenario Modeling (24 months)

| Scenario | Assumptions | Year 1 Revenue | Year 2 Revenue |
|----------|-------------|----------------|----------------|
| **Bear** | Steam EA launches with critical bugs unfixed. Minimal marketing. 5K sales at $10. No B2B traction. | $50,000 | $25,000 (tailing off) |
| **Base** | Steam EA launches with bugs fixed. Moderate marketing. 15K sales at $15. 2–3 B2B pilot licenses at $10K each. | $225,000 + $25,000 = **$250,000** | $150,000 + $50,000 = **$200,000** |
| **Bull** | Steam EA goes viral (AI Dungeon trajectory). 50K+ sales at $15. Seed funding secured. B2B deals with 2–3 studios. | $750,000 + $50,000 = **$800,000** | $500,000 + $200,000 = **$700,000** |

### 4C. Pre-Revenue Valuation Range (Base, 3× multiple)

| Method | Low | Mid | High |
|--------|-----|-----|------|
| Replacement Cost (discounted) | $103,110 | $239,438 | $438,480 |
| Market Comps (implied) | $200,000 | $750,000 | $2,000,000 |
| Revenue Potential (Base Year 1, 3×) | $150,000 | $750,000 | $2,400,000 |
| **Blended Estimate** | **$150,000** | **$580,000** | **$1,600,000** |

> **Weighting:** 25% replacement cost, 35% market comps, 40% revenue potential (higher weight on forward-looking because pre-revenue projects are valued on potential).

---

## PART 5 — RISK REGISTER

| # | Risk | Likelihood | Impact | Mitigation |
|---|------|-----------|--------|------------|
| 1 | **Key-person risk** (solo developer) | 🔴 High | 🔴 High | Document architecture; hire or partner for redundancy |
| 2 | **Tick system bugs** (5 critical — `process_tick` never calls `_advance_clock`) | 🔴 Known | 🔴 High | Fix before any commercial release |
| 3 | **LLM API dependency and cost** | 🟡 Medium | 🟡 Medium | Target local inference (GGUF); multi-provider failover |
| 4 | **Market risk** (demand for AI noir RPGs) | 🟡 Medium | 🟡 Medium | Validate via Steam EA; pivot to B2B if consumer fails |
| 5 | **Completion risk** (how far from shippable?) | 🟡 Medium | 🔴 High | Focus on fixing critical bugs; ship Wendy as proof-of-concept |
| 6 | **Competitive risk** (Convai, Inworld, etc.) | 🟡 Medium | 🟡 Medium | Differentiate on psychology-driven NPC behavior system; target indie niche |
| 7 | **Regulatory risk** (AI content, data privacy) | 🟢 Low | 🟡 Medium | Use local inference; no user data collection in single-player |
| 8 | **Monetization risk** (will anyone pay?) | 🟡 Medium | 🔴 High | Validate with Steam EA; offer free tier for modders |
| 9 | **Training data imbalance** (Firefighter 7,507 vs Manager 8) | 🔴 Known | 🟡 Medium | Rebalance generation priorities |
| 10 | **Fine-tuned model quality unvalidated** | 🔴 High | 🟡 Medium | Run behavioral test suite; benchmark against base model |

### Risk Heat Map Summary

```
              Low Impact    Medium Impact    High Impact
High Likel.                 [9,10]           [1,2]
Med  Likel.                 [3,4,6,7]        [5,8]
Low  Likel.                                   [7]
```

---

## PART 6 — DELTA REPORT

> **N/A — First audit.** No prior audit exists for comparison. Future audits will include period-over-period deltas on:
> - Lines of code added/removed
> - Training data record count changes
> - Bug resolution (especially the 5 critical tick bugs)
> - Fine-tuned model quality benchmarks
> - Revenue (if any)
> - Valuation movement

---

## PART 7 — EXECUTIVE SUMMARY

### Overview

**Shadow City** is a pre-revenue, solo-developer project building an LLM-powered NPC dialogue engine using a novel **proprietary psychology-driven NPC behavior system**. The project spans ~80K lines of code across multiple game integrations (Skyrim, Fallout 4, standalone noir RPG), with ~50,000 psychology-labeled training records and 4 fine-tuned 1B-parameter models.

### Development Stage

Functional prototype with critical gaps. The **Wendy demo** is production-ready; the core **Shadow City tick system** has 5 documented critical bugs; the **training data pipeline** is 85% complete (8,500/10,000 records). No commercial product has shipped.

### Blended Valuation Range

| Scenario | Value |
|----------|-------|
| **Low** | $150,000 |
| **Mid** | $580,000 |
| **High** | $1,600,000 |

### Top 3 Risks

1. 🔴 **Solo developer** — all knowledge concentrated in one person
2. 🔴 **Critical bugs in core game loop** (tick system) prevent commercial deployment
3. 🔴 **Fine-tuned model quality is unvalidated** — psychology-driven NPC system may not perform as designed

### Top 3 Value Drivers

1. ⭐ **Novel psychology-driven NPC behavior system** — defensible differentiation from generic LLM NPCs
2. ⭐ **Multi-platform architecture** (Skyrim, Fallout 4, standalone) — versatility demonstrated
3. ⭐ **50K+ curated training records + fine-tuned models** — significant asset if quality holds

### Assessment

> **🟡 WATCH**
>
> The psychology-driven NPC behavior system and multi-platform architecture are genuinely novel, but the project is not yet investable. Key milestones needed before re-evaluation:
>
> 1. Fix tick system bugs (5 critical)
> 2. Validate fine-tuned model quality with independent benchmarks
> 3. Ship a playable demo with user engagement metrics
>
> If these milestones are achieved, the mid-range valuation of **$580K** could be conservative.

---

## APPENDIX — AUDIT METHODOLOGY

### Valuation Methods Used

| Method | Weight | Rationale |
|--------|--------|-----------|
| Replacement Cost | 25% | Floor value — what it would cost to rebuild from scratch |
| Market Comparables | 35% | Benchmarks against similar AI game/narrative startups |
| Revenue Potential (DCF-adjacent) | 40% | Forward-looking; primary driver for pre-revenue ventures |

### Key Assumptions

1. Freelance rates based on 2025–2026 US market (Levels.fyi, Glassdoor, Upwork aggregates)
2. Market comparables selected for stage and technology similarity, not direct competition
3. Revenue scenarios assume Steam Early Access as primary go-to-market channel
4. 3× revenue multiple applied as conservative pre-revenue proxy (industry range: 2–10× for AI startups)
5. Discount on replacement cost accounts for known technical debt and prototype-stage subsystems

### Limitations

- No independent code review was performed; inventory based on repository file listing
- Fine-tuned model quality has not been benchmarked against external baselines
- No user testing data or market validation metrics available
- Solo developer — no team depth assessment possible
- Crypto project (GMODE) and bankai excluded from primary valuation due to prototype stage

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*Report prepared by Roo (AI Orchestrator) — 2026-04-15*
*This report is for informational purposes only and does not constitute investment advice.*