b8b5e9d6ef
- Increase default batch size from 5 to 20 patterns per CLI call - Add parallel execution with 3 concurrent workers (configurable) - Add ai_enhancement settings to config_manager: - local_batch_size: patterns per Claude CLI call (default: 20) - local_parallel_workers: concurrent CLI calls (default: 3) - Expected speedup: 6-12x faster for large codebases Config settings can be changed via: skill-seekers config (coming soon) or editing ~/.config/skill-seekers/config.json Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
266 lines
9.5 KiB
Markdown
266 lines
9.5 KiB
Markdown
# Spyke Games - Skill Seekers Integration Notes
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> Discussion notes for Claude Code + Skill Seekers integration at Spyke Games
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> Date: 2026-01-06
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---
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## Current State Analysis
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### What They Have (Excellent Foundation)
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```
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knit-game-client/docs/
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├── workflows/
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│ └── feature-development-workflow.md # Complete dev workflow
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├── templates/
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│ ├── ANALYSIS-CHECKLIST.md # 13-section feature analysis
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│ ├── DESIGN-TEMPLATE.md # Feature design template
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│ ├── TDD-TEMPLATE.md # Technical design doc
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│ ├── PR-CHECKLIST.md # Review checklist with pitfalls
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│ └── ISSUE-TEMPLATE.md # GitHub issue structure
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└── features/
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└── area-cover-blocker/ # Example complete feature
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├── DESIGN.md # 549 lines, comprehensive
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├── EDGE-CASES.md
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├── TASKS.md
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└── TDD.md
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```
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### Key Observations
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1. **Already using Claude Code skill references** in docs:
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- `/knitgame-core` - Core gameplay patterns
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- `/threadbox-blocker` - Grid blocker patterns
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2. **Documented Common Pitfalls** (PR-CHECKLIST.md):
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- UnityEngine in Controller/Model (MVC violation)
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- Stale references after async
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- Memory leaks from events (missing Dispose)
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- Animation ID leaks (missing try-finally)
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- Missing PrepareForReuse state reset
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- Double-despawn race conditions
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- Play-on under-restoration
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3. **MVC Layer Rules** (CRITICAL):
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| Layer | UnityEngine | Purpose |
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|-------|-------------|---------|
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| Model | NO | Pure C# data, state, logic |
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| Controller | NO | Business logic, orchestration |
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| View | YES | MonoBehaviour, visuals |
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| Service | YES | Business logic needing Unity APIs |
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4. **Test Patterns**:
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- Reflection-based DI injection (no Zenject in tests)
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- NSubstitute for mocking
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- Real models, mocked dependencies
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---
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## Proposed Skill Layer Architecture
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### Layer 1: Workflow Skills (HOW to develop)
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| Skill | Source | Purpose |
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|-------|--------|---------|
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| `yarn-flow-workflow` | `docs/workflows/` | Feature development lifecycle |
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| `yarn-flow-analysis` | `ANALYSIS-CHECKLIST.md` | Feature analysis patterns |
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| `yarn-flow-pr-review` | `PR-CHECKLIST.md` | Review checklist, pitfalls |
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| `yarn-flow-testing` | Test files + templates | Test patterns, reflection DI |
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### Layer 2: Pattern Skills (WHAT to implement)
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| Skill | Source | Purpose |
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|-------|--------|---------|
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| `yarn-flow-mvc` | Workflow docs + code | MVC layer rules |
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| `yarn-flow-blockers` | Blocker implementations | Grid/Yarn/Bottom patterns |
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| `yarn-flow-boosters` | Booster implementations | Booster patterns |
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| `yarn-flow-async` | Code patterns | UniTask, cancellation, safety |
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| `yarn-flow-pooling` | Generators | ObjectPool, PrepareForReuse |
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| `yarn-flow-events` | Controllers | Event lifecycle (Init/Dispose) |
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| `yarn-flow-di` | Installers | Zenject binding patterns |
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### Layer 3: Reference Skills (Examples to follow)
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| Skill | Source | Purpose |
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|-------|--------|---------|
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| `yarn-flow-threadbox` | ThreadBox implementation | Reference grid blocker |
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| `yarn-flow-mystery` | Mystery implementation | Reference yarn blocker |
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| `yarn-flow-areacover` | AreaCover + DESIGN.md | Recent, fully documented |
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---
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## Proposed Agent Architecture
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### 1. Feature Analysis Agent
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```
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Trigger: "analyze feature {X}" or "what base class for {X}"
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Skills: yarn-flow-analysis, yarn-flow-blockers, yarn-flow-boosters
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Action:
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- Runs ANALYSIS-CHECKLIST programmatically
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- Identifies feature type (Grid/Yarn/Bottom Blocker, Booster)
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- Suggests base class
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- Maps system interactions
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- Identifies edge cases
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- Outputs gap analysis
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```
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### 2. Design Document Agent
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```
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Trigger: "create design doc for {X}" or when starting new feature
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Skills: yarn-flow-workflow, yarn-flow-blockers, yarn-flow-reference
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Action:
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- Creates docs/features/{feature}/DESIGN.md from template
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- Pre-populates interaction matrix based on feature type
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- Suggests edge cases from similar features
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- Creates EDGE-CASES.md skeleton
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```
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### 3. PR Review Agent
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```
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Trigger: PR created, "review PR", or pre-commit hook
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Skills: yarn-flow-pr-review, yarn-flow-mvc, yarn-flow-async
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Action:
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- Scans for UnityEngine imports in Controller/Model
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- Verifies IInitializable + IDisposable pair
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- Checks event subscription/unsubscription balance
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- Validates PrepareForReuse resets all state
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- Checks async safety (CancellationToken, try-finally)
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- Verifies test coverage for public methods
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Output: Review comments with specific line numbers
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```
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### 4. Code Scaffold Agent
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```
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Trigger: "implement {type} {name}" after design approved
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Skills: yarn-flow-blockers, yarn-flow-di, yarn-flow-pooling
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Action:
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- Generates Model extending correct base class
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- Generates Controller with IInitializable, IDisposable
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- Generates ModelGenerator with ObjectPool
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- Generates View (MonoBehaviour)
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- Adds DI bindings to installer
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- Creates test file skeletons
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Output: Complete scaffold following all patterns
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```
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---
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## New Grad Pipeline Vision
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```
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FEATURE REQUEST
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↓
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┌─────────────────────────────────────────┐
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│ 1. ANALYSIS AGENT │
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│ "Analyze feature ThreadCutter" │
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│ → Suggests GridBlockerBaseModel │
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│ → Maps interactions │
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│ → Identifies 12 edge cases │
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└─────────────────────────────────────────┘
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↓
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┌─────────────────────────────────────────┐
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│ 2. DESIGN AGENT │
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│ "Create design doc" │
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│ → Generates DESIGN.md (80% complete) │
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│ → New grad fills in specifics │
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└─────────────────────────────────────────┘
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↓
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┌─────────────────────────────────────────┐
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│ 3. CODE SCAFFOLD AGENT │
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│ "Implement ThreadCutter" │
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│ → Generates 6 files with patterns │
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│ → All boilerplate correct │
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│ → New grad fills in business logic │
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└─────────────────────────────────────────┘
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↓
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┌─────────────────────────────────────────┐
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│ 4. NEW GRAD CODES │
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│ Has correct structure │
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│ Just writes the actual logic │
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│ Skills loaded = answers questions │
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└─────────────────────────────────────────┘
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↓
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┌─────────────────────────────────────────┐
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│ 5. PR REVIEW AGENT │
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│ "Review my PR" │
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│ → Catches MVC violations │
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│ → Verifies async safety │
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│ → Checks test coverage │
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│ → Feedback before human review │
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└─────────────────────────────────────────┘
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↓
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SENIOR-QUALITY CODE FROM JUNIOR DEV
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```
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---
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## Implementation Priority
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### Phase 1: Core Skills (Week 1)
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1. Generate skill from `knit-game-client` repo (full codebase)
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2. Generate skill from `docs/` folder specifically
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3. Install to Claude Code for all devs
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### Phase 2: Specialized Skills (Week 2)
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1. Split into workflow vs pattern skills
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2. Create reference skills from best implementations
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3. Test with actual feature development
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### Phase 3: Agents (Week 3-4)
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1. PR Review Agent (highest ROI - catches common pitfalls)
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2. Analysis Agent (helps new devs start correctly)
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3. Code Scaffold Agent (reduces boilerplate time)
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### Phase 4: CI/CD Integration (Week 5+)
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1. PR Review Agent as GitHub Action
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2. Auto-regenerate skills when docs change
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3. Team-wide skill distribution
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---
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## Questions to Resolve
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1. **Confluence Integration**
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- How stale is Confluence vs docs/ folder?
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- Should we scrape Confluence or focus on in-repo docs?
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- Can we set up sync from Confluence → docs/ → skills?
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2. **Skill Granularity**
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- One big `yarn-flow` skill vs many small skills?
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- Recommendation: Start with 2-3 (workflow, patterns, reference)
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- Split more if Claude context gets overloaded
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3. **Agent Deployment**
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- Local per-developer vs team server?
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- GitHub Actions integration?
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- Slack/Teams notifications?
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4. **SDK Skills**
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- Which SDKs cause most pain?
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- Firebase? Analytics? Ads? IAP?
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- Prioritize based on integration frequency
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---
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## Related Discussions
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- Layered skill architecture (game → framework → external → base)
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- New grad onboarding goal: "produce code near our standard"
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- Manual review → automated agent review pipeline
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- Confluence freshness concerns
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---
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## Next Steps
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1. [ ] Generate skill from knit-game-client repo
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2. [ ] Test with actual feature development
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3. [ ] Identify highest-pain SDK for skill creation
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4. [ ] Design PR Review Agent prompt
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5. [ ] Pilot with 1-2 developers
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