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/adapter-configurationnpx skills add TanStack/ai --skill adapter-configurationgit 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 | $0.00227 | $0.05351 |
| Opus 5 | $0.00113 | $0.02676 |
| Sonnet 5 | $0.00045 | $0.01070 |
| Haiku 4.5 | $0.00023 | $0.00535 |
Grade A, and why
ai-core/adapter-configuration 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 yesterday.
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 — 482 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adapter Configuration
Dependency: This skill builds on ai-core. Read it first for critical rules.
Before implementing: Ask the user which provider and model they want. Then fetch the latest available models from the provider's source code (check the adapter's model metadata file, e.g.
packages/ai-openai/src/model-meta.ts) or from the provider's API/docs to recommend the most current model. The model lists in this skill and its reference files may be outdated. Always verify against the source before recommending a specific model.
Setup
Create an adapter and use it with chat():
import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { openaiText } from '@tanstack/ai-openai'
const stream = chat({
adapter: openaiText('gpt-5.2'),
messages,
modelOptions: {
temperature: 0.7,
max_output_tokens: 1000,
},
})
return toServerSentEventsResponse(stream)
The adapter factory function takes the model name as a string literal and an
optional config object (API key, base URL, etc.). The model name is passed
into the factory, not into chat().
Sampling options (temperature, token limits, top_p/topP, etc.) live
inside modelOptions using each provider's native key — they are not
top-level options on chat(). See the per-provider table in
Configuring Sampling below.
Core Patterns
1. Adapter Selection
Each provider has a dedicated package with tree-shakeable adapter factories. The text adapter is the primary one for chat/completions:
| Provider | Package | Factory | Env Var |
|---|---|---|---|
| OpenAI | @tanstack/ai-openai |
openaiText |
OPENAI_API_KEY |
| Anthropic | @tanstack/ai-anthropic |
anthropicText |
ANTHROPIC_API_KEY |
| Gemini | @tanstack/ai-gemini |
geminiText |
GOOGLE_API_KEY or GEMINI_API_KEY |
| Grok (xAI) | @tanstack/ai-grok |
grokText |
XAI_API_KEY |
| Groq | @tanstack/ai-groq |
groqText |
GROQ_API_KEY |
| OpenRouter | @tanstack/ai-openrouter |
openRouterText |
OPENROUTER_API_KEY |
| Ollama | @tanstack/ai-ollama |
ollamaText |
OLLAMA_HOST (default: http://localhost:11434) |
| Bedrock | @tanstack/ai-bedrock |
bedrockText |
BEDROCK_API_KEY or AWS_BEARER_TOKEN_BEDROCK |
| BytePlus | @tanstack/ai-byteplus |
byteplusText |
ARK_API_KEY (falls back to BYTEPLUS_API_KEY) |
| OpenAI-compatible | @tanstack/ai-openai/compatible |
openaiCompatible / openaiCompatibleText |
provider-specific (passed via apiKey) |
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 482 lines · 227 tokens per session scan A e068f8dcedd9
ai-core/adapter-configuration is a skill published in the GitHub repository TanStack/ai (3,045 stars, last pushed 2d ago), licensed MIT. It adds 227 tokens to every session and 5,351 once invoked, about $0.0011 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.
Other skills, from other repositories
keybindings-help
Use when the user wants to customize keyboard shortcuts, rebind keys, add chord bindings, or modify /.claude/keybindings.json. Examples: "rebind ctrl+s", "add a chord shortcut", "change the submit key", "customize keybindings".
options
Present multiple design options as a vertical stack of anchored turns.
tmux
Remote-control tmux sessions for interactive CLIs by sending keystrokes and scraping pane output.
summarize
Summarize or extract text/transcripts from URLs, podcasts, and local files (great fallback for “transcribe this YouTube/video”).
github
Interact with GitHub using the gh CLI. Use gh issue, gh pr, gh run, and gh api for issues, PRs, CI runs, and advanced queries.
workflow-authoring
Reference for writing a Workflow tool script (script API and gotchas, resume, quality patterns, worked examples). Load before authoring a script for a workflow the user already opted into; it does not itself authorize running one.