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/tanstack/ai/locksnpx skills add TanStack/ai --skill locksgit clone --depth 1 https://github.com/TanStack/aiWhat 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 | $0.00112 | $0.01178 |
| Opus 5 | $0.00056 | $0.00589 |
| Sonnet 5 | $0.00022 | $0.00236 |
| Haiku 4.5 | $0.00011 | $0.00118 |
Grade A, and why
ai-core/locks 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 2d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Locks (coordination — not persistence)
Dependency note: This skill builds on ai-core and ai-core/middleware.
withLocksis a ChatMiddleware that provides a capability. Locks are not part ofAIPersistence.storesand are not composed withcomposePersistence— they ship in@tanstack/ai, independent of@tanstack/ai-persistence.
Why separate?
State stores answer "what is durable chat data?"
Locks answer "who may run this critical section right now?"
withPersistence does not automatically lock a whole turn. Take a
per-thread (or other) lock yourself when multi-writer races matter.
Wire locks
import { withLocks, InMemoryLockStore } from '@tanstack/ai/locks'
middleware: [
withLocks(new InMemoryLockStore()), // single process
]
Alongside persistence — optional, locks do not require it:
import { withLocks, InMemoryLockStore } from '@tanstack/ai/locks'
import { withPersistence } from '@tanstack/ai-persistence'
middleware: [withPersistence(persistence), withLocks(new InMemoryLockStore())]
withLocks provides LocksCapability for downstream middleware (e.g.
sandbox). Order: usually state first, locks alongside or after depending on
who consumes the capability.
The contract
interface LockStore {
withLock<T>(key: string, fn: (signal: AbortSignal) => Promise<T>): Promise<T>
}
InMemoryLockStore ships in @tanstack/ai/locks: a per-key promise chain,
correct within a single process only. Multi-instance deployments need a
distributed implementation — you write it. The Cloudflare Durable Object recipe
is in ai-persistence/build-cloudflare-adapter (@tanstack/ai-persistence).
Type your own store with defineLock (autocomplete, no : LockStore
annotation), then hand it to withLocks. Acquire the key, run fn, release when
fn settles:
import { defineLock, withLocks } from '@tanstack/ai/locks'
import { acquire } from './my-lock-backend'
const locks = defineLock({
async withLock(key, fn) {
const { release, signal } = await acquire(key)
try {
return await fn(signal)
} finally {
release()
}
},
})
middleware: [withLocks(locks)]
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.
- 2d ago First seen · 144 lines · 112 tokens per session scan A a825b51e182c
ai-core/locks is a skill published in the GitHub repository TanStack/ai (3,045 stars, last pushed 2d ago), licensed MIT. It adds 112 tokens to every session and 1,178 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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