Best use case
debug-memory is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
It is a strong fit for teams already working in Codex.
Query and manage the executable feedback debug memory
Teams using debug-memory should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/debug-memory/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How debug-memory Compares
| Feature / Agent | debug-memory | Standard Approach |
|---|---|---|
| Platform Support | Codex | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Query and manage the executable feedback debug memory
Which AI agents support this skill?
This skill is designed for Codex.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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 - @$AIWG_ROOT/agentic/code/addons/ralph/schemas/debug-memory.yaml - Debug memory schema - @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/rules/executable-feedback.md - Executable feedback rules - @$AIWG_ROOT/agentic/code/addons/ralph/docs/executable-feedback-guide.md - Guide
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