Defines the abstract interface for harness adapters. It encapsulates the logic for transforming canonical Markdown definitions into harness-specific formats (TOML, JSON, MDC). This component demonstrates high craftsmanship by isolating harness-specific logic, allowing new AI platforms to be supported by implementing a single interface without modifying the core generation engine.

Implements the LLM-based evaluation layer for the plugin quality framework. It uses anchored rubrics to score plugins on dimensions like triggering accuracy and orchestration fitness. This component is reusable for any system requiring automated quality scoring of AI-generated content or agent behaviors, demonstrating a sophisticated approach to LLM-as-a-judge.

Contains the security enforcement layer using Cedar policies for PreToolUse/PostToolUse hooks. It generates Ed25519-signed receipts for every tool call, enabling tamper-evident audit trails. This is a critical reusable pattern for building secure, compliant AI agents that require human approval gates and cryptographic verification of actions.

Defines the core workflow for track-based development. It orchestrates a multi-stage pipeline (scan, architect, implement, review, QA) with state management and loop guards. This pattern is reusable for managing complex AI-assisted development tasks, ensuring structured progress and human checkpoints in automated workflows.