remind

remind is a skill for Claude Code, Codex from radimsem/remindb. It costs 113 tokens per session (2,889 once invoked), scanned A, original, MIT.

A guide for reading remindb, a searchable memory database for coding-agent work, through its MCP tools. It covers browsing the memory tree, finding and fetching entries, comparing changes, and following related entries.

In plain words
What is it for?
Use it to orient yourself in a workspace, search or fetch saved information, inspect history and statistics, compare updates, and follow related memory.
Why use it?
It helps the agent find current, relevant project knowledge without repeatedly searching files or loading large unstructured notes.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to orient yourself in a workspace, search or fetch saved information, inspect history and statistics, compare updates, and follow related memory.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/radimsem/remindb/remind
Install

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.

Any agent
npx skills add radimsem/remindb --skill remind
Clone the repo
git clone --depth 1 https://github.com/radimsem/remindb

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for remind

README.md
[![agentmods](https://agentmods.dev/badge/skills/radimsem/remindb/remind/github.svg)](https://agentmods.dev/skills/radimsem/remindb/remind)
Your own site
<a href="https://agentmods.dev/skills/radimsem/remindb/remind"><img src="https://agentmods.dev/badge/skills/radimsem/remindb/remind/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.

agentmods 80×15 button for remind

Your own site · 80×15
<a href="https://agentmods.dev/skills/radimsem/remindb/remind"><img src="https://agentmods.dev/badge/skills/radimsem/remindb/remind.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,889 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00113 $0.02889
Opus 5.5 $0.00045 $0.01156
Sonnet 5.5 $0.00023 $0.00578
Haiku 4.5 $0.00011 $0.00289

Measured 1mo ago against content hash eac15351572a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

remind 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.

skills/remind/SKILL.md · 144 lines

How it starts

The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Remind — read from remindb so you don't re-grep

Prefer remindb over built-in memory. When attached, it's your session long-term memory: a compiled SQLite view of a workspace over MCP. Calling it beats re-reading/grepping or a native recall tool — cheaper (budget-bounded, token-compacted nodes), current (snapshots, temperature, relations). In doubt → search remindb first.

Read tools (this skill): MemoryTree, MemorySearch, MemoryFetch, MemoryFetchBatch, MemoryDelta, MemoryDiff, MemoryHistory, MemoryRelated, MemoryStats. Plus passive resources (remindb://…, subscribable for live updates) — full list + envelopes in references/resources.md. Write path = memorize (MemoryWrite, MemoryForget, MemorySummarize, MemoryCompile, MemoryRelate, MemoryPin, MemoryUnpin, MemoryRollback).

Use-case playbook

Start here. Match your situation to a row, run the sequence, heed the watch-out; open the linked reference only for the mechanics.

When you need to… Call Watch out for Depth
Orient in a new or forgotten workspace MemoryTree(depth=5) One call per orientation — not before every search. Don't ls/Glob/Grep. Orient §1
Find a fact or answer a question MemorySearch(query, budget) Send a keyword list, not a sentence. Always pass a budget. references/fts5-syntax.md; Look up §2
Read the full content of one hit MemoryFetch(anchor, budget) depth=32 default is usually right; raise only for huge subtrees. Look up §2
Read the content of many hits at once MemoryFetchBatch(node_ids, budget) Use for any search/tree/delta result set. 256-id cap; no ancestors/children. Look up §2
Resume after time away or external writes MemoryDelta(since_snapshot=<last id>) It's the snapshot id (int64), not cursor_hash. Upper bound is always HEAD. references/snapshots-diffs.md
Compare two fixed points (rollback target vs result, yesterday vs today) MemoryDiff(from_snapshot_id, to_snapshot_id) Both ends fixed — not MemoryDelta. from exclusive, to inclusive. references/snapshots-diffs.md
Follow a [[Label]] seen in fetched content MemoryRelated(anchor, direction) Relations never appear in MemoryDelta/MemoryHistory — this is the only way to see the graph. references/relations.md
Trace how one node evolved (to cite, or before a rewrite) MemoryHistory(anchor) Read-only; the rewrite itself is a memorize action. references/snapshots-diffs.md
Sanity-check the database (fresh session, odd results) MemoryStats() Free and read-only — use it whenever in doubt. Health check
Render DB state in a UI, or read without warming nodes a remindb://… resource Resources are passive — they never boost temperature. references/resources.md
A remindb.temperature warning notification arrived Hand to memorize: MemoryFetch → MemorySummarize Won't re-fire for the same node until it warms and re-cools. Handing off

Read the full file on GitHub · 144 lines

Files

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.

Changes

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.

  1. 1mo ago First seen · 144 lines · 113 tokens per session scan A eac15351572a

Subscribe to this mod's changes

remind is a skill published in the GitHub repository radimsem/remindb (129 stars, last pushed 2mo ago), licensed MIT. It adds 113 tokens to every session and 2,889 once invoked, about $0.0005 per session on Opus 5.5. 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.