--- title: AI SDK tools description: The outbound tools as a tool set for the AI SDK, keyed by tool name and ready to pass to generateText or streamText. sidebar: label: AI SDK related: - /docs/tools - /docs/tools/untrusted-content - /guides/agent-tools --- `aiSdkTools(outbound)` from `outbound-sdk/tools/ai-sdk` returns the [tools](/docs/tools) as one AI SDK tool per outbound tool, keyed by tool name. Pass the object as `tools` to `generateText` or `streamText`. This subpath imports `ai`, which is an optional peer dependency: version 6 or 7. Install it only if you import this subpath. See [installation](/docs/installation). `aiSdkTools` takes the same `only` and `extra` options as [`createTools`](/docs/tools#options). ## Build the tools and run one ```ts title="ai-sdk.ts" import { createOutbound } from "outbound-sdk"; import { demoData, memory } from "outbound-sdk/memory"; import { aiSdkTools } from "outbound-sdk/tools/ai-sdk"; const outbound = createOutbound({ adapter: memory({ data: demoData(), workspaceId: "acme" }), }); // One AI SDK tool per outbound tool, keyed by tool name. const tools = aiSdkTools(outbound, { only: ["campaign_overview", "sender_health"], }); console.log(Object.keys(tools)); const overview = tools.campaign_overview; console.log(overview?.description); // What the AI SDK does when the model calls the tool, done by hand here. const result = await overview?.execute?.( { status: "paused" }, { context: undefined, messages: [], toolCallId: "call_1" } ); console.log(JSON.stringify(result, null, 2)); // A failure is a result the model can read, not an exception. const failed = await overview?.execute?.( { client: "acme" }, { context: undefined, messages: [], toolCallId: "call_2" } ); console.log(JSON.stringify(failed)); ``` ```text title="Output" [ 'campaign_overview', 'sender_health' ] How every campaign is doing right now: sends, replies, positive replies, bounces and reply rate for each campaign with the given status. One vendor request per campaign. Rates are computed from counts; a null means the vendor does not report that count. { "data": { "campaigns": [ { "campaign": "memory:acme:cmp_agencies", "channel": "email", "name": "Agency owners", "metrics": { "bounce_rate": 0.0667, "bounced": 4, "connections_accepted": null, "connections_sent": null, "contacted": 60, "opened": 18, "positive": 0, "positive_reply_rate": 0, "replied": 1, "reply_rate": 0.0167, "reply_rate_basis": "contacted", "sent": 60 }, "status": "paused" } ] }, "meta": { "evidence": "exact", "provider": "memory", "requests": 1, "today": "2026-11-14" }, "next": "Pick another of the listed tools to go further.", "ok": true } {"error":{"code":"Invalid","message":"campaign_overview: \"client\" is not an input. It takes: from, limit, status, to"},"next":"Check the input and try again.","ok":false} ``` Each tool has a `description`, an `inputSchema` built from the tool's JSON Schema, and an `execute` function that returns the tool's result object. A failed tool returns `{ ok: false }` from `execute`. It does not throw, so the AI SDK passes the failure to the model as an ordinary tool result. ## Wiring it to a model ```ts title="generate.ts" import { generateText, stepCountIs } from "ai"; import type { LanguageModel } from "ai"; import type { OutboundApi } from "outbound-sdk"; import { aiSdkTools } from "outbound-sdk/tools/ai-sdk"; /** * Asks a model a question about `outbound`. The model may call the tools, * read what they return and answer, in up to five steps. */ export const ask = ( outbound: OutboundApi, model: LanguageModel, prompt: string ) => generateText({ model, prompt, stopWhen: stepCountIs(5), tools: aiSdkTools(outbound), }); ``` `ask` takes the instance, a model and a question. `stopWhen: stepCountIs(5)` gives the model up to five steps, so it can call a tool, read the result and answer inside one `generateText` call. ## A real run This function was run against a real model on 2026-11-14: `deepseek/deepseek-v4-flash`, through the Vercel AI Gateway, with `ai` 7. The outbound side was the in-memory adapter's demo data, so the run shows a model calling the tools and answering from what they return. It says nothing about a vendor. This is the transcript of that run: the question, each tool call the model made, and its answer. ```json title="Transcript of one live run" { "answer": "There is currently one active campaign:\n\n**Q4 SaaS founders** (`cmp_founders`, email channel)\n- Sends: 90\n- Replies: 7 (7.8% reply rate)\n\nNotes: 52 of the 90 sends were opened, 3 were positive, and 1 bounced. The account has no other campaigns in the active state right now.\n\nWant me to dig into this campaign at all — e.g., what's driving the replies, deliverability, or how many leads it has left?", "model": "deepseek/deepseek-v4-flash", "prompt": "Which campaigns are active, and how many sends and replies has each had?", "ranAt": "2026-11-14", "steps": 2, "toolCalls": [ { "input": { "status": "active" }, "tool": "campaign_overview" } ], "via": "Vercel AI Gateway" } ``` > **An example run, not a recorded output** > > A model does not answer the same way twice, so the test suite does not > reproduce this transcript, and it is not checked on every commit the way the > other outputs on this site are. The run is `site/test/live/ai-sdk.live.ts` in > the repository; `npm run site:live` repeats it with an AI Gateway credential > and asserts that the model called a tool and named the campaign from the > tool's result. Only `ai` 7 was run; `ai` 6 is accepted by the peer range and > was not. The first live run found a problem that is now fixed. The model does not know today's date, so it asked for 2024 to 2026 and found no data. Every tool result now carries `meta.today`, and the date inputs tell the model to leave the range out for the whole history and not to guess. ## Reply text A model given `reply_samples` can ask for reply text. It comes back truncated and marked as untrusted. See [untrusted content](/docs/tools/untrusted-content).