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
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 skills add TanStack/ai --skill debug-logginggit clone --depth 1 https://github.com/TanStack/aiWrote 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/debug-logging)<a href="https://agentmods.dev/skills/tanstack/ai/debug-logging"><img src="https://agentmods.dev/badge/skills/tanstack/ai/debug-logging/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/debug-logging"><img src="https://agentmods.dev/badge/skills/tanstack/ai/debug-logging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00104 | $0.02627 |
| Opus 5.5 | $0.00042 | $0.01051 |
| Sonnet 5.5 | $0.00021 | $0.00525 |
| Haiku 4.5 | $0.00010 | $0.00263 |
Grade A, and why
ai-core/debug-logging 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.
How it starts
The opening of the file, as written. The whole thing — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug Logging
Dependency note: This skill builds on ai-core. Read it first for critical rules.
Use this skill when you need to turn debug logging on or off, narrow what's
printed, or pipe logs into a custom logger (pino, winston, etc.). The same
debug option works on every activity — chat(), summarize(),
generateImage(), generateSpeech(), generateTranscription(),
generateVideo().
Turn it on
import { chat } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
const messages = [{ role: 'user' as const, content: 'Hello' }]
const stream = chat({
adapter: openaiText('gpt-5.5'),
messages,
debug: true, // all categories on, prints to console
})
Each log line is prefixed with an emoji and [tanstack-ai:<category>]:
📤 [tanstack-ai:request] 📤 activity=chat provider=openai model=gpt-5.2 messages=1 tools=0 stream=true
🔁 [tanstack-ai:agentLoop] 🔁 run started
📥 [tanstack-ai:provider] 📥 provider=openai type=response.output_text.delta
📨 [tanstack-ai:output] 📨 type=TEXT_MESSAGE_CONTENT
Turn it off
import { chat } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
const messages = [{ role: 'user' as const, content: 'Hello' }]
chat({
adapter: openaiText('gpt-5.5'),
messages,
debug: false, // silence everything, including errors
})
Omitting debug is not the same as debug: false. When omitted, the
errors category is still on (errors are cheap and important). Use
debug: false or debug: { errors: false } for true silence.
DebugOption — the accepted shapes
import type { Logger } from '@tanstack/ai'
// As exported by '@tanstack/ai'
type DebugOption = boolean | DebugConfig
interface DebugConfig {
// Per-category flags. Any flag omitted from a DebugConfig defaults to true.
request?: boolean
provider?: boolean
output?: boolean
middleware?: boolean
tools?: boolean
agentLoop?: boolean
config?: boolean
errors?: boolean
// Optional custom logger. Defaults to ConsoleLogger.
logger?: Logger
}
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.
- 1mo ago Changed · +82 lines d39ed80fa2c6
- 1mo ago First seen · 264 lines · 104 tokens per session scan A fe2fdf233e27
ai-core/debug-logging is a skill published in the GitHub repository TanStack/ai (3,196 stars, last pushed today), licensed MIT. It adds 104 tokens to every session and 2,627 once invoked, about $0.0004 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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