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 rmarquesa/agentmemory-offline --skill remembergit clone --depth 1 https://github.com/rmarquesa/agentmemory-offlineWrote 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/rmarquesa/agentmemory-offline/remember)<a href="https://agentmods.dev/skills/rmarquesa/agentmemory-offline/remember"><img src="https://agentmods.dev/badge/skills/rmarquesa/agentmemory-offline/remember/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/rmarquesa/agentmemory-offline/remember"><img src="https://agentmods.dev/badge/skills/rmarquesa/agentmemory-offline/remember.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00052 | $0.00502 |
| Opus 5.5 | $0.00021 | $0.00201 |
| Sonnet 5.5 | $0.00010 | $0.00100 |
| Haiku 4.5 | $0.00005 | $0.00050 |
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 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.
This is a copy
95% identical to remember — 9 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
The user wants to save this to long-term memory: $ARGUMENTS
Quick start
memory_save {
"content": "We rotate JWT refresh tokens on every use; the old token is revoked server-side in auth/refresh.ts.",
"concepts": "jwt-refresh-rotation, token-revocation, auth-flow",
"files": "src/auth/refresh.ts"
}
Expected output:
Saved memory abc12345 with 3 concepts: jwt-refresh-rotation, token-revocation, auth-flow.
Why
A memory is only as useful as the terms that retrieve it. Tag with specific
concepts so a future recall finds it, and preserve the user's own phrasing.
Workflow
- Pull the core insight, decision, or fact out of
$ARGUMENTS. - Extract 2-5 lowercased concept phrases. Prefer specific over generic
(
jwt-refresh-rotationbeatsauth). - Extract referenced file paths (absolute or repo-relative). Empty if none.
- Call
memory_savewithcontent,concepts(comma-separated string), andfiles(comma-separated string). - Confirm the save and echo the concepts so the user knows the retrieval terms.
Anti-patterns
WRONG: concepts: "stuff, code, notes" (generic tags nothing can find later).
RIGHT: concepts: "jwt-refresh-rotation, token-revocation" (specific, retrievable).
Checklist
- Content preserves the user's phrasing, not a paraphrase.
- Concepts are specific, lowercased, 2-5 items.
- File paths are real references, not guesses.
- Confirmation echoes the exact concepts tagged.
See also
recall: retrieve what you save here (the pair to this skill).forget: remove a memory you saved by mistake.
Troubleshooting
See ../_shared/TROUBLESHOOTING.md if memory_save is not available.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 First seen · 62 lines · 52 tokens per session scan A f68701ff5cdf
remember is a skill published in the GitHub repository rmarquesa/agentmemory-offline (0 stars, last pushed 14d ago), licensed Apache-2.0. It adds 52 tokens to every session and 502 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to remember, differing in 9 lines, and is treated as a copy.
Other skills, from other repositories
plur-create-engrams
Create or improve PLUR engrams from conversations, documents, decisions, observations, and explicit preferences. Use for memory extraction, engram authoring, or reviewing proposed memories, including global, scoped, pinned, retrieved, and provisional knowledge. Ordinary use of existing memories does not require this…
plur-memory
Persistent learning for AI agents. Open engram format. Your agent learns from corrections, remembers across sessions, and transfers knowledge across domains.
plur-session-end
Extract durable learnings at the end of a session. Saves corrections, preferences, and codebase patterns as engrams — nothing ephemeral, nothing sensitive.
plur-memory
Your memory stays on your machine. No cloud, no tracking, no API key. PLUR makes your OpenClaw remember — and shares that memory with every other tool you use.
engraphis-memory
Give the agent durable, scoped, explainable memory across sessions and repositories through the Engraphis MCP tools. Use when you learn a convention, decision, bug cause/fix, or user preference worth keeping; when prior context would help before you answer or act (to avoid re-asking or re-deriving); when asked "why is…
card-refresh
Use when refreshing stale Brigade memory cards from the care refresh queue - category allowlist, grounded edits that cite on-disk sources of truth, archive-only retention, and reinforce-in-place instead of near-duplicate siblings (#724). Never delete, remove, or prune.