# Changelog

All notable changes to mycontext will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [0.2.0] - 2026-02-09

### 🎉 Major Release - Complete Context Engineering Platform

#### Added
- **50 Cognitive Patterns** - Research-backed reasoning templates
  - 6 Analysis patterns (QuestionAnalyzer, DataAnalyzer, TrendIdentifier, GapAnalyzer, SWOTAnalyzer, AnomalyDetector)
  - 5 Reasoning patterns (StepByStepReasoner, AnalogicalReasoner, CausalReasoner, RootCauseAnalyzer, HypothesisGenerator)
  - 5 Decision patterns (DecisionFramework, ComparativeAnalyzer, TradeoffAnalyzer, MultiObjectiveOptimizer, CostBenefitAnalyzer)
  - 5 Creative patterns (IdeaGenerator, Brainstormer, InnovationFramework, DesignThinker, MetaphorGenerator)
  - 7 Communication patterns (SimplificationEngine, ClarityOptimizer, AudienceAdapter, PersuasionFramework, NarrativeBuilder, TechnicalTranslator, FeedbackComposer)
  - 5 Planning patterns (ScenarioPlanner, StakeholderMapper, PrioritySetter, DeadlineManager, ResourceAllocator)
  - 6 Problem Solving patterns (ProblemDecomposer, BottleneckIdentifier, ConstraintOptimizer, DependencyMapper, EfficiencyAnalyzer, TradeSpaceExplorer)
  - 11 Specialized patterns (CodeReviewer, ContentOutliner, SocraticQuestioner, IntentRecognizer, AmbiguityResolver, RiskAssessor, RiskMitigator, ImpactAssessor, ConflictResolver, ConceptExplainer, SynthesisBuilder)

- **Transformation Engine** - Automatic pattern selection
  - Input analysis (type, complexity, domain detection)
  - Automatic pattern recommendation
  - Confidence scoring
  - `transform()` convenience function for one-line transformations

- **Quality Metrics System** - Measurable context improvement
  - 6 quality dimensions (Clarity, Completeness, Specificity, Relevance, Structure, Efficiency)
  - Overall quality scoring (0.0-1.0)
  - Before/after comparison
  - Actionable improvement suggestions
  - Quality reports

- **13 Export Formats** - Universal compatibility
  - Data formats: JSON, YAML, XML, Markdown, Dictionary
  - LLM providers: OpenAI, Anthropic, Google (Gemini)
  - AI frameworks: LangChain, LlamaIndex, CrewAI, AutoGen
  - Messages format for universal use

- **6 Integration Helpers** - Framework compatibility
  - LangChainHelper - LangChain message conversion
  - LlamaIndexHelper - LlamaIndex prompt conversion
  - CrewAIHelper - CrewAI agent creation
  - AutoGenHelper - AutoGen assistant creation
  - DSPyHelper - DSPy prompt conversion
  - SemanticKernelHelper - Semantic Kernel templates
  - `auto_integrate()` function for automatic detection

- **Comprehensive Testing** - Production quality
  - 59 tests total (100% pass rate)
  - 37 core functionality tests
  - 12 stress/performance tests
  - 10 real-world scenario tests
  - Performance benchmarks: 100 executions in 5.6ms

- **Complete Documentation**
  - Professional README with full API reference
  - 2 Jupyter notebooks (getting_started, complete_guide)
  - Contribution guidelines
  - Examples for all major use cases

#### Changed
- **Organized Pattern Structure** - 8 logical categories
  - Moved all patterns to category-based folders
  - Added category __init__.py files
  - Maintained backward compatibility
  - Improved discoverability

- **Enhanced Core Classes**
  - Context: Added 8 new export methods
  - Pattern: Improved base class functionality
  - Guidance: Enhanced with style parameter

- **Improved Package Structure**
  - Clean root directory (6 essential files only)
  - Organized examples/ folder
  - Organized tests/ folder
  - Removed empty folders
  - Professional .gitignore

#### Performance
- Pattern instantiation: 458ms for all 50 patterns
- Execution speed: 0.06ms average per pattern
- Quality evaluation: <1ms per context
- Export operations: <10ms for all formats

#### Breaking Changes
None - Fully backward compatible with v0.1.0

## [0.1.0] - 2026-02-08

### Added
- Initial project structure
- Foundation layer (Directive, Guidance, Constraints)
- Structure layer (Pattern, Blueprint)
- Core Context class
- Provider interface with mock provider
- Comprehensive test suite (37 tests)
- Documentation and examples
- Revolutionary Context Stack™ framework
- Context as Code™ paradigm
- Clean, intuitive API
- Type-safe with Pydantic models
- Production-ready architecture

[0.2.0]: https://github.com/SadhiraAI/mycontext/releases/tag/v0.2.0
[0.1.0]: https://github.com/SadhiraAI/mycontext/releases/tag/v0.1.0
