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/memtomem/memtomem/recallnpx skills add memtomem/memtomem --skill recallgit clone --depth 1 https://github.com/memtomem/memtomemWrote 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/memtomem/memtomem/recall)<a href="https://agentmods.dev/skills/memtomem/memtomem/recall"><img src="https://agentmods.dev/badge/skills/memtomem/memtomem/recall.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 | $0.00033 | $0.00273 |
| Opus 5 | $0.00016 | $0.00137 |
| Sonnet 5 | $0.00007 | $0.00055 |
| Haiku 4.5 | $0.00003 | $0.00027 |
Grade A, and why
recall 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 4d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- memtomem-recall — 89% identical, 6 lines differ
What it actually says
Recall memories
Use $ARGUMENTS as the date range or recent-memory request.
If the request does not clearly specify the date range or recent-memory request, ask before calling a tool — and
in a non-interactive context (a subagent or scripted run with nobody to ask), do not
stall and do not guess: stop and report insufficient_input naming the missing date range or recent-memory request.
A request that does specify the date range or recent-memory request proceeds normally in either context.
Translate relative dates such as “last week” into since and until values when possible, then call mem_recall. Preserve any source, namespace, scope, or result-limit constraint from the request.
Present memories newest first with their creation date and source. Ask for a date range only when the request provides no usable temporal constraint. Use topic search, not recall, when the user is asking what a memory says rather than when it was created.
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.
- 4d ago First seen · 18 lines · 33 tokens per session scan A b0a6bd4b3133
recall is a skill published in the GitHub repository memtomem/memtomem (13 stars, last pushed today), licensed Apache-2.0. It adds 33 tokens to every session and 273 once invoked, about $0.0002 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.
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