aiwg
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Cognitive architecture for AI-augmented software development with structured memory, ensemble validation, and closed-loop correction. FAIR-aligned artifacts, 84% cost reduction via human-in-the-loop, standards adopted by 100+ organizations.
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---
description: Query and manage the executable feedback debug memory
category: code-quality
---
# Debug Memory Command
Query, analyze, and manage the debug memory from executable feedback loops.
## Instructions
Manage the debug memory stored in `.aiwg/ralph/debug-memory/`:
### Subcommand: query
Search debug memory for relevant past execution sessions.
1. Search `.aiwg/ralph/debug-memory/sessions/` for matching entries
2. Match by file path, error type, test name, or keyword
3. Display relevant sessions with fix attempts and outcomes
4. Highlight reusable patterns
### Subcommand: patterns
Display learned patterns from past debug sessions.
1. Load `.aiwg/ralph/debug-memory/patterns/learned-patterns.yaml`
2. Show pattern frequency, success rate, and applicability
3. Suggest patterns applicable to current context
### Subcommand: stats
Show aggregate statistics from debug memory.
1. Total sessions, pass rate, average attempts
2. Most common error types
3. Most effective fix patterns
4. Files with highest failure frequency
### Subcommand: clear
Clear debug memory (with confirmation).
1. Prompt for confirmation
2. Archive current memory to `.aiwg/ralph/debug-memory/archive/`
3. Reset sessions and patterns
## Arguments
- `query [keyword]` - Search debug memory
- `patterns` - Show learned patterns
- `stats` - Show aggregate statistics
- `clear` - Clear and archive debug memory
- `--file [path]` - Filter by source file
- `--error [type]` - Filter by error type
- `--since [date]` - Filter by date
## References
- @agentic/code/addons/ralph/schemas/debug-memory.yaml - Debug memory schema
- @.claude/rules/executable-feedback.md - Executable feedback rules
- @.aiwg/ralph/docs/executable-feedback-guide.md - Guide