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/chat-experiencenpx skills add TanStack/ai --skill chat-experiencegit 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 | $0.00078 | $0.06192 |
| Opus 5 | $0.00039 | $0.03096 |
| Sonnet 5 | $0.00016 | $0.01238 |
| Haiku 4.5 | $0.00008 | $0.00619 |
Grade A, and why
ai-core/chat-experience 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 — 768 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chat Experience
This skill builds on ai-core. Read it first for critical rules.
Setup — Minimal Chat App
Server: API Route (TanStack Start)
// src/routes/api.chat.ts
import { createFileRoute } from '@tanstack/react-router'
import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
export const Route = createFileRoute('/api/chat')({
server: {
handlers: {
POST: async ({ request }) => {
const abortController = new AbortController()
const body = await request.json()
const { messages } = body
const stream = chat({
adapter: openaiText('gpt-5.5'),
messages,
systemPrompts: ['You are a helpful assistant.'],
abortController,
})
return toServerSentEventsResponse(stream, { abortController })
},
},
},
})
Client: React Component
// src/routes/index.tsx
import { useState } from 'react'
import { useChat, fetchServerSentEvents } from '@tanstack/ai-react'
import type { UIMessage } from '@tanstack/ai-react'
function ChatPage() {
const [input, setInput] = useState('')
const { messages, sendMessage, isLoading, error, stop } = useChat({
connection: fetchServerSentEvents('/api/chat'),
})
const handleSubmit = () => {
if (!input.trim()) return
sendMessage(input.trim())
setInput('')
}
return (
<div>
<div>
{messages.map((message: UIMessage) => (
<div key={message.id}>
<strong>{message.role}:</strong>
{message.parts.map((part, i) => {
if (part.type === 'text') {
return <p key={i}>{part.content}</p>
}
return null
})}
</div>
))}
</div>
{error && <div>Error: {error.message}</div>}
<div>
<input
value={input}
onChange={(e) => setInput(e.target.value)}
onKeyDown={(e) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault()
handleSubmit()
}
}}
disabled={isLoading}
placeholder="Type a message..."
/>
{isLoading ? (
<button onClick={stop}>Stop</button>
) : (
<button onClick={handleSubmit} disabled={!input.trim()}>
Send
</button>
)}
</div>
</div>
)
}
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 · 768 lines · 78 tokens per session scan A 48625b5612ce
ai-core/chat-experience is a skill published in the GitHub repository TanStack/ai (3,056 stars, last pushed today), licensed MIT. It adds 78 tokens to every session and 6,192 once invoked, about $0.0004 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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