create-client-tool

MUST be used whenever creating an AtlasTool (client-side tool) for an Atlas agent. Do NOT manually write AtlasTool definitions or wire them into useAtlasChat — this skill handles the TypeBox schema, execute function, and hook wiring. This includes tools that fetch data, render UI, call APIs, show charts, query local state, or perform any browser-side action. Triggers: AtlasTool, client tool, add tool, create tool, new tool, tool definition, agent tool.

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Install skill "create-client-tool" with this command: npx skills add cognitedata/dune-skills/cognitedata-dune-skills-create-client-tool

Create a Client Tool

Scaffold a new AtlasTool named $ARGUMENTS and wire it into the app.

Background

Client tools let the Atlas Agent invoke logic that runs in the browser — rendering charts, querying local state, showing UI panels, triggering navigation, etc. The agent decides when to call the tool; the app executes it and returns a result.

The flow is:

  1. Agent responds with a clientTool action
  2. The library validates the arguments against the TypeBox schema
  3. execute() runs in the browser and returns { output, details }
  4. output (string) is sent back to the agent as the tool result
  5. details (any shape) is available on message.toolCalls for the UI to render

Step 1 — Understand the codebase

Before writing anything, read:

  • The file where useAtlasChat is called (likely src/App.tsx) to find where tools is passed
  • Any existing tool definitions to match the file/naming conventions

Step 2 — Define the tool

Create the tool as a typed constant. Use Type from @cognite/dune-industrial-components/atlas-agent to define the parameters schema — this gives both compile-time types and runtime validation.

import { Type } from "@cognite/dune-industrial-components/atlas-agent";
import type { AtlasTool } from "@cognite/dune-industrial-components/atlas-agent";

export const myTool: AtlasTool = {
  name: "my_tool",            // snake_case — this is what the agent uses to invoke it
  description:
    "One sentence describing what this tool does and when the agent should call it.",
  parameters: Type.Object({
    exampleParam: Type.String({ description: "What this param is for" }),
    optionalNum: Type.Optional(Type.Number({ description: "..." })),
  }),
  execute: async (args) => {
    // args is fully typed from the schema above
    // Do the work here — call APIs, update state, render UI, etc.
    return {
      output: "Plain text summary sent back to the agent",
      details: {
        // Any structured data you want available in the UI via message.toolCalls
      },
    };
  },
};

TypeBox quick reference

SchemaUsage
Type.String()string
Type.Number()number
Type.Boolean()boolean
Type.Literal("foo")exact value
Type.Union([Type.Literal("a"), Type.Literal("b")])enum
Type.Array(Type.String())string[]
Type.Object({ ... })object
Type.Optional(...)mark any field optional

Always add a description to each field — the agent uses these to understand what to pass.


Step 3 — Wire into useAtlasChat

Find the useAtlasChat call and add the tool to the tools array:

const { messages, send, ... } = useAtlasChat({
  client: isLoading ? null : sdk,
  agentExternalId: AGENT_EXTERNAL_ID,
  tools: [myTool],   // add here
});

Step 4 — Render tool results (if needed)

If the tool returns structured details, render them in the message list. message.toolCalls is a ToolCall[] — one entry per tool call (client-side and server-side) in call order.

{msg.toolCalls?.map((tc, i) => (
  // tc.name    — tool name
  // tc.output  — the string sent back to the agent
  // tc.details — your structured data (cast to your known shape)
  <MyToolOutput key={i} data={tc.details as MyToolDetails} />
))}

Done

The agent can now invoke $ARGUMENTS. Describe what it does clearly in the description field — the agent relies on that string to decide when and how to call the tool.

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