TanStack AI is a TypeScript SDK for building applications that stream AI responses, call tools, run agents, produce structured output, and handle multimodal or realtime interactions. Developers use it across frameworks and AI providers through shared typed interfaces and provider adapters. The catalogue entries are add-ons for working with this SDK.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/TanStack/ainpx agentmods add skills/tanstack/ai/build-drizzle-adapterWrote 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/tanstack/ai/build-drizzle-adapter)<a href="https://agentmods.dev/skills/tanstack/ai/build-drizzle-adapter"><img src="https://agentmods.dev/badge/skills/tanstack/ai/build-drizzle-adapter/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.
<a href="https://agentmods.dev/skills/tanstack/ai/build-drizzle-adapter"><img src="https://agentmods.dev/badge/skills/tanstack/ai/build-drizzle-adapter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 40 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 5.1 | $0.00079 | $0.05620 |
| Opus 5.5 | $0.00032 | $0.02248 |
| Sonnet 5.5 | $0.00016 | $0.01124 |
| Haiku 4.5 | $0.00008 | $0.00562 |
Grade A, and why
ai-persistence/build-drizzle-adapter 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 24d 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 — 608 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Drizzle Chat Persistence
The deliverable is one file in the app — src/lib/chat-persistence.ts —
exporting a ChatPersistence built from the app's existing Drizzle db. Plus
four tables added to the app's existing schema file and a migration generated
through the app's existing drizzle-kit setup.
Do not create a package, a second db instance, a migration runner, or a
drizzle.config.ts. The app has those.
Read the Store Reference
(docs/persistence/store-reference.md) for the store contracts and
invariants, and ai-persistence/stores for the shape rules. Every
store below mirrors the reference in-memory backend in
@tanstack/ai-persistence (memory.ts); the shared conformance testkit is the
proof.
1. Read the app before writing anything
| Find | Where to look | What it decides |
|---|---|---|
| Dialect | drizzle.config.ts dialect:, or the drizzle-orm/*-core import |
sqlite-core vs pg-core vs mysql-core column builders |
| Schema file(s) | drizzle.config.ts schema: glob |
Where the four tables go — append, never start a new file |
The db handle |
src/db/index.ts, src/db.ts, src/server/db.ts |
Module singleton (export const db) vs factory (getDb()) |
| Migration flow | drizzle.config.ts out:, the migrations/ or drizzle/ journal |
Which generate/apply commands to tell the user to run |
| Naming conventions | Existing tables in the schema file | Table prefix, var casing, snake_case column names |
| Import alias | tsconfig.json paths |
@/db, ~/db, #/db/index, or a relative path |
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.
- 24d ago Changed · +45 lines 005f1b274da5
- 1mo ago Changed ddeac456b175
- 1mo ago First seen · 563 lines · 79 tokens per session scan A 27ea133fdc65
ai-persistence/build-drizzle-adapter is a skill published in the GitHub repository TanStack/ai (3,203 stars, last pushed today), licensed MIT. It adds 79 tokens to every session and 5,620 once invoked, about $0.0003 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.
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