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/radimsem/remindb/memorizenpx skills add radimsem/remindb --skill memorizegit clone --depth 1 https://github.com/radimsem/remindbWrote 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/radimsem/remindb/memorize)<a href="https://agentmods.dev/skills/radimsem/remindb/memorize"><img src="https://agentmods.dev/badge/skills/radimsem/remindb/memorize.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 | $0.00120 | $0.01999 |
| Opus 5 | $0.00060 | $0.01000 |
| Sonnet 5 | $0.00024 | $0.00400 |
| Haiku 4.5 | $0.00012 | $0.00200 |
Grade A, and why
memorize 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.
How it starts
The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memorize — write to remindb so it indexes well
Prefer remindb over built-in memory. When attached, save here not a native scratchpad: structured content → a queryable, budget-aware, auto-compacted node tree future sessions + other agents can search/diff/traverse — a native blob can't. Author it the right way and every future read is cheaper.
Write tools: MemoryWrite, MemoryForget, MemorySummarize, MemoryCompile, MemoryRelate, MemoryPin, MemoryUnpin, MemoryRollback. Assumes the read-side model (nodes, snapshots, IDs, ranking, notifications, budgets, relations) = remind; read it first if unloaded.
Two ways to write — pick by content shape ★
The decision that determines index quality, because MemoryWrite does not parse: it stores your payload as exactly one flat text node (raw, no headings/lists/tree, no TOON/MathML compaction). Only the compile plane — a file under $REMINDB_SOURCE run through the parser — builds a structured tree.
| New/updated memory is… | Write it as | Result |
|---|---|---|
| Structural — has a heading, list, code/table, or ≥2 distinct facts | a file under $REMINDB_SOURCE, placed where it topically belongs → compile |
parsed multi-node subtree |
| A single text update to an existing anchor | MemoryWrite(anchor, payload) |
that node's content replaced in place |
| A single new text fact | MemoryWrite(payload) |
one flat text node |
Any block structure → file. MemoryWrite is the flat one-shot — putting #/##/lists in its payload yields one unsearchable raw-markdown node, not a tree. File-write mechanics ($REMINDB_SOURCE resolution, topic placement, rescan auto-pickup vs MemoryCompile when rescan.enabled:false, incremental emit) → references/write-paths.md.
Use-case playbook
Match the situation, run the sequence, heed the watch-out. Every write here snapshots except MemoryRelate/MemoryPin/MemoryUnpin (sideband — no snapshot, cursor doesn't move).
What ships with it
4 files 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.
- 4d ago First seen · 98 lines · 120 tokens per session scan A 304a20429bfc
memorize is a skill published in the GitHub repository radimsem/remindb (125 stars, last pushed 1mo ago), licensed MIT. It adds 120 tokens to every session and 1,999 once invoked, about $0.0006 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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