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 ashish7802/awesome-api-skills --skill vercel-ai-sdkgit clone --depth 1 https://github.com/ashish7802/awesome-api-skillsWrote 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/ashish7802/awesome-api-skills/vercel-ai-sdk)<a href="https://agentmods.dev/skills/ashish7802/awesome-api-skills/vercel-ai-sdk"><img src="https://agentmods.dev/badge/skills/ashish7802/awesome-api-skills/vercel-ai-sdk/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/ashish7802/awesome-api-skills/vercel-ai-sdk"><img src="https://agentmods.dev/badge/skills/ashish7802/awesome-api-skills/vercel-ai-sdk.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00528 |
| Opus 5.5 | $0.00000 | $0.00211 |
| Sonnet 5.5 | $0.00000 | $0.00106 |
| Haiku 4.5 | $0.00000 | $0.00053 |
Grade A, and why
vercel-ai-sdk 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vercel AI SDK Skill
Overview
The Vercel AI SDK (ai) is the standard TypeScript toolkit for building AI applications, agents, and streaming user interfaces across OpenAI, Anthropic, Google Gemini, DeepSeek, and Groq using a unified provider architecture.
Installation
npm install ai zod @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google
Authentication
Each model provider loads its corresponding environment variable automatically on the server:
OPENAI_API_KEYfor@ai-sdk/openaiANTHROPIC_API_KEYfor@ai-sdk/anthropicGOOGLE_GENERATIVE_AI_API_KEYfor@ai-sdk/google
Core Concepts
generateText/streamText: Unified text generation and token streaming with multi-step tool calling (maxSteps).generateObject/streamObject: Deterministic structured JSON generation validated against azodschema.useChat/useCompletion: React hooks for streaming UI states and tool invocations.
Common Workflows
- Define a route handler
/api/chatusingstreamText. - Configure
toolswithzodparameter schemas andexecuteasync handlers. - Return
result.toDataStreamResponse()to stream text and tool calls to the frontend.
AI Pitfalls
- Hallucinating v2/v3 APIs: Never import
OpenAIStreamorStreamingTextResponse. Those were removed in AI SDK v4. Always usestreamTextandresult.toDataStreamResponse(). - Missing
maxStepson agentic loops: When tools have anexecutefunction, setmaxSteps: 5onstreamTextso the SDK automatically feeds tool outputs back to the model. - Unvalidated JSON: Use
generateObject({ model, schema: z.object(...) })rather than regex-parsing markdown code blocks.
Production Checklist
- Using
aiv4+ core primitives (streamText,generateObject) - Provider packages (
@ai-sdk/openai,@ai-sdk/anthropic) installed and configured server-side - Route handlers return
result.toDataStreamResponse() -
maxDurationexported in serverless route files to prevent timeout on long streams
What ships with it
2 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 · 40 lines · 0 tokens per session scan A 41179fe73f40
vercel-ai-sdk is a skill published in the GitHub repository ashish7802/awesome-api-skills (13 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 528 tokens. 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 2026-10-22.
Other skills, from other repositories
cost-aware-llm-pipeline
A planning guide for choosing language models and managing the amount of conversation context used by an AI coding workflow. It groups tasks by complexity and gives rules for avoiding context overflow during long sessions.
natural
Render the provided prompt template with Jinja context and send it to the active NPC's LLM. The rendered text becomes the user prompt; the LLM response is placed in context['output'].
awesome-chatgpt
Search this repository's awesome-ChatGPT-repositories list for open-source ChatGPT and LLM projects such as RAG frameworks, agents, chatbots, CLIs, prompts, and browser extensions. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, or AI development; not for editing or adding list…
llm-integration
LLM integration patterns for function calling, streaming responses, local inference with Ollama, and fine-tuning customization. Use when implementing tool use, SSE streaming, local model deployment, LoRA/QLoRA fine-tuning, or multi-provider LLM APIs.
happyhorse-prompter
A tool for writing short prompts for HappyHorse 1.0, an AI video generator that can create video with sound. Its prompts put the main subject first, specify the camera, and describe audible sound when needed.
kling-prompter
A prompt-writing guide for Kling 3.0, a video-generation model. It covers short videos, story-driven videos with dialogue or sound, and animating an existing reference image.