Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jmagly/aiwg --skill debug-memorygit clone --depth 1 https://github.com/jmagly/aiwgWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jmagly/aiwg/debug-memory)<a href="https://agentmods.dev/skills/jmagly/aiwg/debug-memory"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/debug-memory/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jmagly/aiwg/debug-memory"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/debug-memory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00011 | $0.00452 |
| Opus 5.5 | $0.00004 | $0.00181 |
| Sonnet 5.5 | $0.00002 | $0.00090 |
| Haiku 4.5 | $0.00001 | $0.00045 |
Grade A, and why
debug-memory scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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.
- Search
.aiwg/ralph/debug-memory/sessions/for matching entries - Match by file path, error type, test name, or keyword
- Display relevant sessions with fix attempts and outcomes
- Highlight reusable patterns
Subcommand: patterns
Display learned patterns from past debug sessions.
- Load
.aiwg/ralph/debug-memory/patterns/learned-patterns.yaml - Show pattern frequency, success rate, and applicability
- Suggest patterns applicable to current context
Subcommand: stats
Show aggregate statistics from debug memory.
- Total sessions, pass rate, average attempts
- Most common error types
- Most effective fix patterns
- Files with highest failure frequency
Subcommand: clear
Clear debug memory (with confirmation).
- Prompt for confirmation
- Archive current memory to
.aiwg/ralph/debug-memory/archive/ - Reset sessions and patterns
Arguments
query [keyword]- Search debug memorypatterns- Show learned patternsstats- Show aggregate statisticsclear- 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/agent-loop/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/agent-loop/docs/executable-feedback-guide.md - Guide
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed 1448d122ed52
- 1mo ago First seen · 67 lines · 11 tokens per session scan A 6cbe0b33f5ca
debug-memory is a skill published in the GitHub repository jmagly/aiwg (224 stars, last pushed today), licensed MIT. It adds 11 tokens to every session and 452 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
ripple
Analyzing pre-change impact across vertical (dependency chains, files) and horizontal (pattern consistency, naming) dimensions. Use to estimate blast radius before a refactor. No code.
sweep
Detecting unnecessary files, unused code, and orphaned files, and proposing safe deletion. Not for removal execution (Builder), repo structure (Grove), or scope cutting (Void).
hive-mind-advanced
Queen-led collective-intelligence coordination with consensus mechanisms and persistent shared memory. Use when orchestrating a large swarm of agents under a lead coordinator, building consensus across agents, or maintaining durable cross-agent memory.
lore
Curating cross-agent knowledge and institutional memory: extracts patterns from agent journals into METAPATTERNS.md, detects knowledge decay, propagates best practices. Use for memory curation.
bolt
Optimizing frontend (re-render, memoization, lazy loading) and backend (N+1, indexing, caching, async) performance, plus continuous auto-tuning loops for GC/threadpool/cache/worker settings.
lens
Comprehending and investigating codebases: structure mapping, feature discovery, data flow tracing for 'does X exist?' or 'how does Y work?'. Includes a conversational ask mode. Does not write code.