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 commands/rmarquesa/agentmemory-offline/remembergit clone --depth 1 https://github.com/rmarquesa/agentmemory-offlineWhat 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 | $0.00000 | $0.00192 |
| Opus 5 | $0.00000 | $0.00096 |
| Sonnet 5 | $0.00000 | $0.00038 |
| Haiku 4.5 | $0.00000 | $0.00019 |
Grade A, and why
remember 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 yesterday.
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.
This is a copy
100% identical to remember — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Explicitly save an insight, decision, or learning to agentmemory for future sessions. Wraps the memory_save MCP tool.
Usage
/remember [what to remember]
Instructions
- Analyze what needs to be remembered — extract the core insight, decision, or fact.
- Extract 2-5 searchable concepts (lowercased keyword phrases). Prefer specific terms ("jwt-refresh-rotation" over "auth").
- Extract relevant file paths the memory references.
- Call
memory_savewith:content— full text to remember (preserve user's phrasing)concepts— extracted concept listfiles— extracted file list (empty array if none)type— choose from: pattern, preference, architecture, bug, workflow, fact
- Confirm the save and show the concepts tagged so the user knows retrieval terms.
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.
- yesterday First seen · 20 lines · 0 tokens per session scan A 8e27caf25ba2
remember is a command published in the GitHub repository rmarquesa/agentmemory-offline (0 stars, last pushed 2d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 192 tokens. A static security scan graded it A with 0 findings. It is 100% identical to remember, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
polish-ui
Polish UI elements by auditing SCSS and TSX markup against the Anytype design system, then fixing discrepancies.
tree-ring-capture
Capture a concise validated lesson decision warning or preference in Tree Ring Memory.
tree-ring-audit
Audit consolidate or forget stale sensitive or superseded Tree Ring Memory entries.
tree-ring-update
Check for or install a verified Tree Ring Memory CLI update without changing installation scope.
tree-ring-certify
Generate Tree Ring harness or recall-quality evidence without confusing it with the full framework release suite.
tree-ring-dox-sync
Preview and synchronize DOX-style AGENTS.md guidance as source-linked Tree Ring memory.