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Agent skill

Tanstack AI Memory In Memory

by TanStack in TanStack/ai

A skill your agent uses when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and…

MITAuto-check passed

Install Tanstack AI Memory In Memory

skills CLI
$ npx skills add TanStack/ai --skill tanstack-ai-memory-in-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install TanStack/ai tanstack-ai-memory-in-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/TanStack/ai.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/ai-memory/skills/tanstack-ai-memory-in-memory .claude/skills/tanstack-ai-memory-in-memory && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tanstack-ai-memory-in-memory
GitHub stars
3.2k
Used in
1 other repo
Token cost
~448 tokens
SKILL.md length
150 words
Files
1
Skills in repo
24
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and…

  • Wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup
  • SKILL.md covers When to use it, When NOT to use it, Setup and Options, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Options (embedder

What it does

Tanstack AI Memory In Memory is an agent skill from TanStack/ai. Use when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and what NOT to use it for (multi-process or persistent).

Its SKILL.md is about 450 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with TanStack and Redis. The repository describes itself as: 🤖 Type-safe, provider-agnostic TypeScript AI SDK for streaming chat, tool calling, agents, and multimodal apps across OpenAI, Anthropic, Gemini, React, Vue, Svelte, and Solid. The licence is MIT.

When your agent uses it

  • Wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup
  • Options (embedder
  • To pick it (dev/tests/single-process demos)
  • What NOT to use it for (multi-process

Example prompts

  • “/tanstack-ai-memory-in-memory”

What it can do on your machine

Read from SKILL.md and the folder at commit 5a41239. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tanstack AI Memory In Memory loads about 448 tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 150 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~448

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TanStack/ai at commit 5a41239, republished under its MIT licence (© TanStack). 150 words, ~448 tokens.

Download SKILL.mdSave it as .claude/skills/tanstack-ai-memory-in-memory/SKILL.md (or your agent's skills folder).
name
tanstack-ai-memory-in-memory
description
Use when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and what NOT to use it for (multi-process or persistent).

In-Memory Memory Adapter

Zero-dependency recall/save adapter backed by a Map. Records vanish on process restart.

When to use it

  • Local development.
  • Vitest / Playwright tests.
  • Single-process demos where users don't need persistence.

When NOT to use it

  • Production multi-process deployments — every worker has its own Map; users get inconsistent memory.
  • Anything that needs survival across restarts.

For production, use redis() (see the tanstack-ai-memory-redis skill).

Setup

ts
import { memoryMiddleware } from '@tanstack/ai-memory'
import { inMemory } from '@tanstack/ai-memory/in-memory'

const memory = inMemory()

// A static scope is fine for dev/tests; derive it from the session in real apps.
memoryMiddleware({
  adapter: memory,
  scope: { threadId: 'demo-thread', userId: 'alice' },
})

Options

inMemory(options?) accepts:

  • topK (default 6), minScore (default 0.15), kinds — recall tuning.
  • embedder: { embed(text): Promise<number[]> } — enable semantic scoring (both recall and save embed through it).
  • extract(turn, scope) — return derived facts to persist alongside the raw turn (e.g. call an LLM to pull out preferences). Without it, save stores the raw user/assistant messages and recall scores them lexically + by recency.
  • render(hits) — replace the built-in prompt renderer.

Capacity

The adapter scans every record in a scope per recall. Fine up to ~100k records; beyond that, switch to Redis.

© TanStack, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in packages/ai-memory/skills/tanstack-ai-memory-in-memory of TanStack/ai.

Open the folder on GitHubat commit 5a41239

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in TanStack/ai, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Tanstack AI Memory In Memory next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tanstack AI Memory In Memory compared with similar skills
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Game Changing FeaturesopenstatusHQ/data-table-filters2.3k3 repos~2.1kAutomated safety check: PassMIT
Frontend Query Mutationlangflow-ai/langflow156k—~979Automated safety check: PassMIT

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Works with

Questions about Tanstack AI Memory In Memory

What does Tanstack AI Memory In Memory do?

A skill your agent uses when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and…. Tanstack AI Memory In Memory is an agent skill from TanStack/ai. Use when wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup, options (embedder, extract, topK/minScore), when to pick it (dev/tests/single-process demos), and what NOT to use it for (multi-process or persistent).

When should I use Tanstack AI Memory In Memory?

Tanstack AI Memory In Memory fits situations like: wiring inMemory() from @tanstack/ai-memory/in-memory — explains setup; options (embedder; to pick it (dev/tests/single-process demos); what NOT to use it for (multi-process.

How do I install Tanstack AI Memory In Memory in Claude Code?

Run `npx skills add TanStack/ai --skill tanstack-ai-memory-in-memory -a claude-code`. Or copy the skill folder (packages/ai-memory/skills/tanstack-ai-memory-in-memory in TanStack/ai) into .claude/skills/tanstack-ai-memory-in-memory in your project. Claude Code loads it when a task matches its description.

How do I install Tanstack AI Memory In Memory in Codex?

Run `npx skills add TanStack/ai --skill tanstack-ai-memory-in-memory -a codex`. Or copy the skill folder (packages/ai-memory/skills/tanstack-ai-memory-in-memory in TanStack/ai) into .agents/skills/tanstack-ai-memory-in-memory in your project. Codex loads it when a task matches its description.

Can I use Tanstack AI Memory In Memory in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TanStack/ai --skill tanstack-ai-memory-in-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tanstack-ai-memory-in-memory, .gemini/skills/tanstack-ai-memory-in-memory, .github/skills/tanstack-ai-memory-in-memory and .opencode/skills/tanstack-ai-memory-in-memory in your project.

What does Tanstack AI Memory In Memory need to run?

SKILL.md names no scripts, command-line tools or credentials: Tanstack AI Memory In Memory is instructions for the agent only.

Does Tanstack AI Memory In Memory access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tanstack AI Memory In Memory safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tanstack AI Memory In Memory use?

Tanstack AI Memory In Memory is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tanstack AI Memory In Memory use?

About 448 tokens (SKILL.md is roughly 1.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tanstack AI Memory In Memory?

Skills that share tags, products or a category with Tanstack AI Memory In Memory: Configuring Horizon (coollabsio/coolify, 63k stars), Native Data Fetching (CherryHQ/cherry-studio-app, 4k stars), Add Redis Command to go-redis (redis/go-redis, 22k stars) and Game Changing Features (openstatusHQ/data-table-filters, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tanstack AI Memory In Memory?

TanStack (a GitHub organization) maintains it in TanStack/ai, which has 3,169 GitHub stars. The repository holds 24 skills in this directory. The repository was last updated on October 7, 2026.

Source: TanStack/ai on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.