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/m-t-d-n/agentmemory-codex-windows/remembernpx skills add M-T-D-N/agentmemory-codex-windows --skill remembergit clone --depth 1 https://github.com/M-T-D-N/agentmemory-codex-windowsWrote 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/m-t-d-n/agentmemory-codex-windows/remember)<a href="https://agentmods.dev/skills/m-t-d-n/agentmemory-codex-windows/remember"><img src="https://agentmods.dev/badge/skills/m-t-d-n/agentmemory-codex-windows/remember.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 | $0.00052 | $0.00609 |
| Opus 5 | $0.00026 | $0.00304 |
| Sonnet 5 | $0.00010 | $0.00122 |
| Haiku 4.5 | $0.00005 | $0.00061 |
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 3d 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
86% identical to remember — 2 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.
How it starts
The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The user wants to save this to long-term memory: $ARGUMENTS
Quick start
memory_save {
"project": "my-project",
"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). In a multi-agent setup passagentIdso the memory lands in the right agent's scope. - Confirm the save and echo the concepts so the user knows the retrieval terms.
- To update a fact, save the corrected version outright: near-duplicate content supersedes the old record, which leaves recall but stays in the version chain.
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.
- Project is the exact registered project, never an inferred sibling path.
- 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.lesson: behavioral rules from corrections; memories are for facts.memory-discipline: when to save unprompted.
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.
- 3d ago First seen · 69 lines · 52 tokens per session scan A 8cee6a44eef2
remember is a skill published in the GitHub repository M-T-D-N/agentmemory-codex-windows (2 stars, last pushed 3d ago), licensed Apache-2.0. It adds 52 tokens to every session and 609 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to remember, differing in 2 lines, and is treated as a copy.
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