Lyra.
Architectural parsing engine. Lyra transforms raw GitHub repositories into high-signal engineering intelligence.
Context 01: The Parser
Codebases are stories; Lyra reads the plot, not just the lines.
— Structural integrity mapping
— Tech-debt indicator detection
— Design pattern extraction
Context 02: The Persona
Bypassing marketing hype to establish technical authority.
● Strict Staff Engineer system-steering
● Pattern-driven insight synthesis
● Senior leadership resonance filtering
System
Architecture
Lyra utilizes Spring AI to manage model interactions and robust system-message steering for architectural consistency.
Integrity Note
"Establish engineering truth by analyzing structural patterns rather than documentation claims."
Repo Mapping
Crawls file trees to identify core architecture and tech-stack fingerprints.
Spring AI Boot
Enterprise-grade orchestration for structured model communication.
CQRS Detection
Identifies decoupling of read/write operations for scalability analysis.
Signal Synthesis
Translates patterns into high-level executive engineering briefs.
Build Specifications
INTEL_NODE_LYRAMOD_01
GHToken Integration
Secure OAuth handshake for deep private repository access.
MOD_02
Persona Steering
High-precision system prompts mimicking senior staff roles.
MOD_03
Bottleneck Analysis
Detects heavy nodes to prevent monolith scaling issues.
MOD_04
Pattern Library
Extensible JSON library for recurring design pattern matching.
MOD_05
Insight Streaming
Real-time response generation with reactive Spring streams.
MOD_06
Audit Export
Structured PDF/JSON output for technical due diligence.