Update the attempt counter example in SPEC.yaml to use substitution-only
template syntax instead of Jinja2 control structures ({% if %}).
The AI can naturally understand attempt context from {{current_attempt}},
{{max_attempts}}, and {{attempts_remaining}} variables without needing
conditional logic in the template itself.
This aligns with the substitution-only template system where logic lives
in scripts and templates only display pre-computed values.
SPEC.yaml fixes:
- Comment out orphaned example code blocks that broke YAML parsing
- Convert progressive hints and dynamic question examples to comments
- Add placeholder keys to maintain valid YAML structure
- All examples now documented but non-executable (reference only)
- Validates with 0 errors
guarded_ai.py refactor (CLI simulator now uses v2.0 features):
- Import activity_utils.py for consistency with activity.py
- Use check_conditions() for advanced metadata conditions (gte, lt, contains, etc.)
- Use filter_content_blocks() for template rendering and conditional blocks
- Use render_template() for dynamic question text with {{variables}}
- Use resolve_conditional_navigation() for if/elif/else navigation
- Use select_weighted_random() for weighted random selection
- Use get_progressive_hint() for progressive hints system
- Create template contexts with built-in variables (current_attempt, etc.)
Benefits:
- Single source of truth for v2.0 logic (activity_utils.py)
- CLI simulator now tests all v2.0 features
- Maintainability: changes to features only need updates in one place
- Consistency: web app and CLI behave identically
All changes validated and tested.
Add comprehensive v2.0 features to enhance activity creation:
Features Implemented:
- Template variables: {{metadata.key}}, {{current_attempt}}, etc.
- Conditional content blocks: show_if conditions for dynamic content
- Advanced metadata conditions: gte, lt, contains, regex, exists operators
- Conditional navigation: if/elif/else branching based on metadata
- Progressive hints system: Auto-display hints based on attempt number
- Weighted random selection: Probabilistic outcomes with custom weights
- Dynamic question text: Questions with template variables
- Built-in attempt counters: Access to current_attempt, max_attempts, attempts_remaining
Files Modified:
- activity.py: Integrated all v2.0 features into activity execution
- activity_utils.py: New utility module for templates and conditions
- activity_yaml_validator.py: Updated validator for v2.0 schema
- CLAUDE.md: Added session persistence and Twitch Plays model docs
- research/SPEC.yaml: Comprehensive v2.0 feature documentation
Added:
- research/activity-test-v2-features.yaml: Test activity demonstrating all features
All changes validated and tested. Zero errors in validator.
- Add random bucket names (emergency, surprise, bonus) to main buckets list
- Fix invalid transition targets to use existing steps
- Add tokens_for_ai to all feedback_prompts (required field)
- Add bonus transition definition
All validation errors resolved - SPEC.yaml now passes validation
Random Bucket System:
- Probabilistic events that trigger alongside user responses
- Random rolls before categorization to prevent AI bias
- Multiple random events can trigger simultaneously
- User bucket processed first, random events layer on top
- Metadata accumulates across all transitions
- Last transition's navigation wins
Implementation:
- activity.py: Core random bucket rolling logic
- activity_yaml_validator.py: Validation for random_buckets config
- research/guarded_ai.py: CLI simulator with random event display
- tests/unit/test_random_buckets.py: 22 comprehensive tests (all passing)
Fashion Empire Enhancement:
- activity40-fashion-empire-backrooms.yaml: Added random events to 4 zones
- fashion_emergency (5%): Urgent crises testing leadership
- creative_opportunity (10%): Breakthroughs rewarding innovation
- surprise_client (5%): VIP visitors recognizing reputation
- Random events enhance gameplay without hijacking user intent
Documentation:
- research/SPEC.yaml: Complete YAML specification with verbose comments
- All metadata operations (string concat, numeric ops, random)
- Random buckets with flow explanation
- Feedback prompts (multi-agent system)
- Processing scripts (pre_script, processing_script)
- Model overrides (classifier_model, feedback_model)
- Termination patterns and best practices
- Validation rules and examples
New Activities:
- activity-nuclear-power-plant-ai.yaml: Nuclear reactor control simulation
- activity-submarine-simulation.yaml: Deep sea exploration
- activity-unwaste-factory.yaml: Recycling facility management
Testing:
✅ All 22 random bucket tests passing
✅ YAML validation passing for all activities
✅ Deterministic triple-trigger test (100% probability)
