---
timestamp: 2025-09-15T18:46:56.725199
type: agent_ops
metadata: {"agent_type": "ops", "agent_id": "ops_acdd2a61-4fd4-4cee-ab6e-dc4ccba95358", "session_id": "acdd2a61-4fd4-4cee-ab6e-dc4ccba95358", "delegation_context": {"description": "Complete EWTN analysis with fixed line counts", "timestamp": "2025-09-15T18:46:56.722334"}}
---


AGENT MEMORY - PROJECT-SPECIFIC KNOWLEDGE:
# Agent Memory: ops
<!-- Last Updated: 2025-08-10 11:39:35 | Auto-updated by: ops -->

<!-- MEMORY LIMITS: 8KB max | 10 sections max | 15 items per section -->

## Project Context
gitflow-analytics: python (with javascript) standard application
- Main modules: gitflow_analytics, gitflow_analytics/classification, gitflow_analytics/metrics, gitflow_analytics/identity_llm
- Testing: Python unittest pattern
- Key patterns: Unit Testing

## Project Architecture
- Standard Application with python implementation
- Main directories: src, tests, docs
- Core modules: gitflow_analytics, gitflow_analytics/classification, gitflow_analytics/metrics, gitflow_analytics/identity_llm

## Coding Patterns Learned
- Python project: use type hints, follow PEP 8 conventions
- Project uses: Unit Testing

## Implementation Guidelines
- Use pip for dependency management
- Follow python unittest pattern
- Follow tests in /tests/ directory
- Key config files: pyproject.toml

## Domain-Specific Knowledge
<!-- Agent-specific knowledge for gitflow-analytics domain -->
- Key project terms: metrics, models, classification, gitflow

## Effective Strategies
<!-- Successful approaches discovered through experience -->

## Common Mistakes to Avoid
- Avoid circular imports - use late imports when needed
- Don't ignore virtual environment - always activate before work
- Don't ignore database transactions in multi-step operations
- Avoid N+1 queries - use proper joins or prefetching

## Integration Points
- Sqlite database integration

## Performance Considerations
- Use list comprehensions over loops where appropriate
- Consider caching for expensive operations
- Index frequently queried columns
- Use connection pooling for database connections

## Current Technical Context
- Tech stack: python
- Data storage: sqlite
- Key dependencies: click>=8.1, gitpython>=3.1, pygithub>=2.0, tqdm>=4.65
- Documentation: README.md, CONTRIBUTING.md, CHANGELOG.md

## Recent Learnings
<!-- Most recent discoveries and insights -->


INSTRUCTIONS: Review your memory above before proceeding. Apply learned patterns and avoid known mistakes.


Complete the EWTN GitFlow Analytics report with the recently fixed line counting that excludes boilerplate files.

Context:
- We've fixed the line counting to exclude boilerplate files (package-lock.json, vendor.js, test files, etc.)
- The fix is working but processing is slower due to pattern matching against 147 exclusion patterns
- Partial cache shows HOSANNA_UI reduced from 105,861 to ~14,283 lines (86% reduction)
- The analysis process was killed after running for several minutes

Tasks:
1. Run the full 4-week analysis for EWTN-test with the fixed code
2. If it's taking too long (>5 minutes), consider optimizing the pattern matching or reducing the exclusion patterns to essential ones
3. Generate the complete reports showing accurate line counts
4. Verify the line counts are reasonable (not inflated by boilerplate)
5. Provide a summary comparing before/after line counts

Location: /Users/masa/Projects/managed/gitflow-analytics/EWTN-test
Command: gitflow-analytics -c config.yaml --weeks 4

Note: The process may take 5-10 minutes due to the exclusion checking. Consider running with nice or in background if needed.

Expected output:
- Narrative report with corrected line counts
- Verification that HOSANNA_UI and CNA_FRONTEND show reasonable line counts
- Summary of the impact of boilerplate exclusion