## 1. Type System & Data Models

- [x] 1.1 Define BotArchetype enum with all 8 archetypes (Nit, TAG, LAG, Maniac, CallingStation, LooseFish, OldMan, MonsterTAG)
- [x] 1.2 Define SkillLevel enum with 5 tiers (Novice, Beginner, Medium, Hard, Ultra)
- [x] 1.3 Extend PlayerSeat type with personality and skillLevel fields
- [x] 1.4 Create PersonalityProfile type with VPIP range, PFR range, bluff frequency, aggression pattern, and timeout default
- [x] 1.5 Create ObservationStats type with VPIP, PFR, FoldToCBet, WTSD, bet sizing profiles, timing data
- [x] 1.6 Extend GameState to include observationData field mapping player IDs to ObservationStats

## 2. Bot Personality Profiles

- [x] 2.1 Implement personality profile for Nit archetype (VPIP 5-15%, PFR 4-12%, low bluff, timeout: fold)
- [x] 2.2 Implement personality profile for TAG archetype (VPIP 15-25%, PFR 10-20%, moderate bluff, timeout: check/fold)
- [x] 2.3 Implement personality profile for LAG archetype (VPIP 25-40%, PFR 20-35%, high bluff, timeout: call)
- [x] 2.4 Implement personality profile for Maniac archetype (VPIP 40-60%, PFR 35-55%, extreme bluff, timeout: raise)
- [x] 2.5 Implement personality profile for Calling Station archetype (VPIP 30-50%, PFR 5-15%, zero bluff, timeout: call)
- [x] 2.6 Implement personality profile for Loose Fish archetype (VPIP 35-50%, PFR 10-20%, low bluff, timeout: call)
- [x] 2.7 Implement personality profile for Old Man archetype (VPIP 10-20%, PFR 3-8%, zero bluff, timeout: call)
- [x] 2.8 Implement personality profile for Monster TAG archetype (VPIP 10-18%, PFR 9-16%, selective bluff, timeout: check)

## 3. Mistake Libraries

- [x] 3.1 Define mistake library for Nit (folds too much, misses value, never bluffs)
- [x] 3.2 Define mistake library for TAG (occasional dominated hand play, slow-plays too often)
- [x] 3.3 Define mistake library for LAG (overbluffs river, wide EP ranges, inconsistent sizing)
- [x] 3.4 Define mistake library for Maniac (bluffs into strength, can't extract value, zero fold ability)
- [x] 3.5 Define mistake library for Calling Station (calls with any pair, never folds post-flop, tiny bets)
- [x] 3.6 Define mistake library for Loose Fish (calls too wide, occasional surprise raise, small bets)
- [x] 3.7 Define mistake library for Old Man (smooth-calls then folds, misses value checks, passive to a fault)
- [x] 3.8 Define mistake library for Monster TAG (rarely misreads, occasionally gets trapped by extreme bluffers)
- [x] 3.9 Implement skill-level error rate mapping (Novice ~40%, Beginner ~25%, Medium ~15%, Hard ~10%, Ultra ~5%)
- [x] 3.10 Implement mistake injection function that samples from archetype library based on skill error rate

## 4. Base Strategy Engine

- [x] 4.1 Implement position-based hand ranking chart for pre-flop decisions (9 positions × hand matrix)
- [x] 4.2 Implement post-flop base strategy using hand strength evaluation vs board texture
- [x] 4.3 Implement pot odds calculation for drawing hand decisions
- [x] 4.4 Implement base bluff frequency calculator based on board and position
- [x] 4.5 Implement base bet sizing recommendations per street

## 5. Bot Decision Pipeline

- [x] 5.1 Implement three-layer pipeline: base strategy → personality filter → skill noise
- [x] 5.2 Implement personality filter that reshapes action probabilities based on archetype profile
- [x] 5.3 Implement skill noise layer that probabilistically overrides decisions with mistakes
- [x] 5.4 Implement timing decision function (archetype × skill determines how long bot "thinks")
- [x] 5.5 Integrate bot decision engine into turn.ts to replace coin-flip logic

## 6. Decision Timer System

- [x] 6.1 Create Timer component with configurable duration and visual countdown display
- [x] 6.2 Implement sequential timer management (starts for current player, advances on action/timeout)
- [x] 6.3 Implement timeout action handler that triggers archetype-appropriate default
- [x] 6.4 Record decision time for every action in action history
- [x] 6.5 Integrate timer into betting round flow with human timer mode support

## 7. Observation Tracking Engine

- [x] 7.1 Implement VPIP tracking (count voluntary pot entries / total hands)
- [x] 7.2 Implement PFR tracking (count pre-flop raises / total hands)
- [x] 7.3 Implement Fold-to-CBet tracking (count folds to continuation bets / total CBet faces)
- [x] 7.4 Implement WTSD tracking (count showdowns / total post-flop participations)
- [x] 7.5 Implement per-street bet sizing tracker with pattern detection (small/standard/polarized)
- [x] 7.6 Implement timing tell tracker (fast vs slow distributions per action type)
- [x] 7.7 Wire observation updates to trigger after each completed hand

## 8. Player Classification Engine

- [x] 8.1 Define weighted scoring functions for all 8 archetypes
- [x] 8.2 Implement confidence calculation based on score magnitude and sample size
- [x] 8.3 Implement minimum sample size check (10 hands before classification)
- [x] 8.4 Implement confidence capping by sample size brackets (10-20: 60%, 20-40: 80%, 40+: uncapped)
- [x] 8.5 Implement secondary pattern detection (bet sizing tendencies, timing tells, bluff frequency)
- [x] 8.6 Integrate classification results into observation data for UI display

## 9. Table Setup UI

- [x] 9.1 Create visual table layout component showing all seats with poker table aesthetic
- [x] 9.2 Implement seat click handler that opens archetype/skill selection dropdown
- [x] 9.3 Implement quick presets (Fish Table, Regular Grind, High Stakes, Training Mix)
- [x] 9.4 Implement global settings panel (blinds, stack size, player count, timer config)
- [x] 9.5 Implement info level selector (None, Hints, Stats, Full Reveal)
- [x] 9.6 Implement feedback level selector (Off, Post-hand, Real-time)
- [x] 9.7 Wire table setup to initialize GameState with configured bot personalities

## 10. Info Display System

- [x] 10.1 Create info display component that renders opponent data based on info level
- [x] 10.2 Implement "None" mode (no data shown)
- [x] 10.3 Implement "Hints" mode (occasional contextual pattern hints)
- [x] 10.4 Implement "Stats" mode (raw VPIP, PFR, Fold-to-CBet, WTSD display)
- [x] 10.5 Implement "Full Reveal" mode (all stats + inferred type + confidence + patterns)
- [ ] 10.6 Wire dynamic updates to refresh after each hand completion

## 11. Teaching Coach System

- [x] 11.1 Create post-hand analysis generator that evaluates player decisions vs optimal play
- [x] 11.2 Implement real-time suggestion engine that references opponent observation data
- [x] 11.3 Implement coaching content filtering based on info level (no stat leakage at lower levels)
- [x] 11.4 Implement pattern recognition confirmation detection (3+ consecutive successful exploitations)
- [x] 11.5 Create "Read Confirmed" notification component with lesson reinforcement
- [x] 11.6 Integrate teaching coach into hand completion flow and decision UI

## 12. Integration & Testing

- [x] 12.1 End-to-end test: full hand plays with personality-driven bot decisions
- [ ] 12.2 End-to-end test: timer expires and triggers correct timeout action per archetype
- [x] 12.3 End-to-end test: observation stats accumulate correctly across multiple hands
- [x] 12.4 End-to-end test: classification produces correct type after sufficient sample size
- [ ] 12.5 End-to-end test: info display respects chosen level and hides/reveals appropriately
- [ ] 12.6 End-to-end test: teaching coach provides feedback matching chosen intensity level
- [x] 12.7 Run svelte-check and fix any type errors