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 agentmods add skills/jmagly/aiwg/ralph-memorynpx skills add jmagly/aiwg --skill ralph-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/ralph-memory)<a href="https://agentmods.dev/skills/jmagly/aiwg/ralph-memory"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/ralph-memory.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00021 | $0.02556 |
| Opus 5 | $0.00010 | $0.01278 |
| Sonnet 5 | $0.00004 | $0.00511 |
| Haiku 4.5 | $0.00002 | $0.00256 |
Grade A, and why
ralph-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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 298 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill access pattern (post-kernel-pivot, 2026.5+)
Skill names referenced in this document are AIWG skills, not slash commands. Most are not kernel-listed and cannot be invoked as
/skill-nameby the platform. Reach them via:aiwg discover "<capability>" aiwg show skill <name>Only kernel-listed skills (
aiwg-doctor,aiwg-refresh,aiwg-status,aiwg-help,use,steward) are directly invokable as slash commands. See skill-discovery rule.
Al Memory
Inspect and manage the semantic memory that Al accumulates across loop iterations. Memory entries record lessons learned, failure patterns, and success patterns so that later iterations — and future loops on similar tasks — benefit from what earlier attempts discovered.
Natural Language Triggers
Users may say:
- "ralph memory"
- "ralph memories"
- "list ralph memory"
- "query ralph memory"
- "what has ralph learned"
- "show ralph lessons"
- "clear ralph memory"
Parameters
Subcommand (required)
One of list, query, or clear.
--loop-id (optional)
Scope the operation to a specific loop's memory. If omitted, operates on the global memory store (.aiwg/ralph/memory.json).
/ralph-memory list --loop-id abc123
--query (optional, used with query subcommand)
Text to search for in memory entries. Matches against lesson, pattern, context, and tags fields.
/ralph-memory query --query "auth mocks"
--since (optional)
Filter entries created on or after this date. Accepts ISO 8601 date (2026-04-01) or relative expressions (7d, 2w).
/ralph-memory list --since 7d
Memory Entry Schema
Each entry in .aiwg/ralph/memory.json follows this structure:
{
"id": "mem_a1b2c3",
"loopId": "abc123",
"iteration": 2,
"createdAt": "2026-04-01T10:42:00Z",
"type": "failure_pattern",
"lesson": "Auth mocks must be initialized inside beforeEach, not at module scope",
"context": "src/auth/auth.test.ts iteration 2 failure",
"tags": ["auth", "mocks", "jest"],
"confidence": 0.9
}
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.
- 6d ago First seen · 298 lines · 21 tokens per session scan A c7a19937a5eb
ralph-memory is a skill published in the GitHub repository jmagly/aiwg (209 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 2,556 once invoked, about $0.0001 per session on Opus 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
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory.
cortivex-context-compression
Compress agent outputs for efficient context handoff between pipeline nodes while preserving actionable information.
agent-v3-memory-specialist
Agent skill for v3-memory-specialist - invoke with $agent-v3-memory-specialist.
hive.note-taking
Maintain a free-form scratchpad of decisions, extracted values, and open questions so context pruning doesn't lose anything you still need.
moai-foundation-context
Manages context window optimization, session state persistence, and token budget allocation for multi-agent workflows. Use for token budget management, context limits, or session handoff across agents.
project-context
Use PowerContext project memory and handoff tools through MCP when continuing prior work, recalling decisions, maintaining durable memory, or transferring work across tasks, sessions, or agents.