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Unit 5: Analyst Lambda - Code Analysis Engine

Objective: Implement the core code analysis engine that processes repositories from Drawer S3 bucket and generates comprehensive analysis using Strands.

Unit Overview

The Analyst Lambda serves as the intelligence core of the CodeRipple pipeline, transforming raw repository data into actionable insights and documentation.

Integration Points:

  • Input: EventBridge repo_ready events from Receptionist
  • Processing: Strands-powered code analysis on repository working copies
  • Output: Analysis results stored in S3 + analysis_ready events to Deliverer

Subunit Breakdown

5.1. Analyst Foundation and EventBridge Integration 5.2. Mock Analysis Implementation 5.3. Analysis Results Storage and Event Publishing 5.4. Performance Optimization and Error Resilience 5.5. Real Strands Integration (Final Implementation)

Technical Considerations

Lambda Configuration:

  • Runtime: Python 3.12
  • Memory: 1GB+ (scalable based on repository size)
  • Ephemeral Storage: 5GB (for large repository processing)
  • Timeout: 15 minutes (maximum Lambda timeout)

Dependencies:

  • Strands analysis engine
  • boto3 for AWS services integration
  • Archive extraction libraries (zip, tar)
  • JSON/YAML processing for configuration

IAM Permissions Required:

  • S3 read access to Drawer bucket workingcopy directory
  • S3 write access to Drawer bucket analysis directory
  • EventBridge publish permissions for analysis_ready events
  • CloudWatch logs write permissions

Event Flow Integration:

Receptionist → repo_ready → Analyst → analysis_ready → Deliverer

Success Criteria

Phase 1: Mock Implementation (Subunits 5.1-5.4)

  1. ✅ Analyst Lambda receives and processes repo_ready events correctly
  2. ✅ Repository working copies downloaded from S3 successfully
  3. ✅ Mock analysis generates simple README.md with "This is a mock analysis for repository {repo-owner}/{repo-name}"
  4. ✅ Analysis results stored in structured S3 analysis directory
  5. ✅ analysis_ready events published for downstream processing
  6. ✅ Component Task Logging Standard implemented throughout
  7. ✅ End-to-end pipeline functional with mock analysis
  8. ✅ Error handling and performance optimized for production use

Phase 2: Production Implementation (Subunit 5.5)

  1. ✅ Real Strands analysis integration replaces mock implementation
  2. ✅ Comprehensive code analysis generates actionable insights
  3. ✅ Production analysis results with real documentation and metrics
  4. ✅ Full CodeRipple pipeline operational with actual analysis capabilities

Mock Analysis Outputs

Sample Mock Results:

  • README.md: "This is a mock analysis for repository {repo-owner}/{repo-name}"

This simplified approach enables complete pipeline testing and development while real Strands integration proceeds independently.

Dependencies

  • Unit 4 Complete: Receptionist and Drawer must be operational
  • Strands Integration: Core analysis engine availability
  • EventBridge: Telephonist configuration for event routing

This unit establishes the intelligence core of the CodeRipple pipeline, transforming repository data into actionable analysis results ready for delivery.