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cognitedata/dune-skills338 installs

integrate-atlas-chat

MUST be used whenever building a chat UI with Atlas agents in a Dune app. Do NOT manually write useAtlasChat integration code — this skill handles installation, component structure, and hook wiring. Triggers: useAtlasChat, atlas chat, streaming chat, agent chat, chat interface, chat component, chat UI. For a full chat app, run skills in order: (1) integrate-atlas-chat, (2) create-client-tool (per tool), (3) setup-python-tools (if Python tools needed).

How do I install this agent skill?

npx skills add https://github.com/cognitedata/dune-skills --skill integrate-atlas-chat
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill facilitates the integration of a streaming chat UI for Atlas agents into Dune applications. It installs official components from the vendor's GitHub repository and sets up the necessary React hooks and components following standard practices. No security risks were identified.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • ZeroLeakspass

    Score: 93/100 · 2 sections analyzed

What does this agent skill do?

Integrate Atlas Agent Chat

Add a streaming Atlas Agent chat UI to this Dune app.

Agent external ID: $ARGUMENTS

Your job

Complete these steps in order. Read each file before modifying it.


Step 1 — Understand the app

Read these files before touching anything:

  • package.json — detect package manager (packageManager field or lock file) and existing deps
  • src/App.tsx (or equivalent entry component) — understand current structure

Step 2 — Install dependencies

Install the package and its required peer deps using the app's package manager:

  • pnpm → pnpm add "github:cognitedata/dune-industrial-components#semver:*" @sinclair/typebox ajv ajv-formats
  • npm → npm install "github:cognitedata/dune-industrial-components#semver:*" @sinclair/typebox ajv ajv-formats
  • yarn → yarn add "github:cognitedata/dune-industrial-components#semver:*" @sinclair/typebox ajv ajv-formats

Step 3 — Build the chat component

Replace (or create) the main App.tsx with a full chat UI. The component must:

  1. Import useAtlasChat and ChatMessage from @cognite/dune-industrial-components/atlas-agent/react
  2. Get the SDK via useDune() from @cognite/dune
  3. Pass null while loading — client: isLoading ? null : sdk
  4. Show streaming text in real time using msg.isStreaming with a blinking cursor
  5. Show tool call events — when progress.startsWith("Executing:"), render it distinctly (e.g. a ⚙ icon + monospace tool name) so tool calls are clearly visible
  6. Show tool calls — each assistant message.toolCalls (after streaming completes) should appear as expandable cards beneath the message
  7. Abort button — show a "Stop" button while isStreaming, wired to abort()
  8. Reset button — "New chat" button wired to reset()
  9. Auto-scroll — scroll to bottom on new messages and progress updates
  10. Auto-resize textarea — expand up to ~120px, submit on Enter, newline on Shift+Enter

Key hook API

import { useAtlasChat } from "@cognite/dune-industrial-components/atlas-agent/react";
import type { ChatMessage } from "@cognite/dune-industrial-components/atlas-agent/react";

const { messages, send, isStreaming, progress, error, reset, abort } = useAtlasChat({
  client: isLoading ? null : sdk,   // null-safe — hook waits for a real client
  agentExternalId: "...",
  tools?: AtlasTool[],              // optional client-side tools
});

// messages[n].role          — "user" | "assistant"
// messages[n].text          — full text (streams chunk-by-chunk via isStreaming)
// messages[n].isStreaming   — true while this message is being written
// messages[n].toolCalls     — ToolCall[] once response is complete (client + server-side, in call order)
// progress                  — e.g. "Agent thinking" or "Executing: get_timeseries"
// isStreaming               — true for the entire duration of a response

Tool call display pattern

// During streaming — show as a distinct "tool call" bubble above the message
{isStreaming && progress?.startsWith("Executing:") && (
  <div>⚙ {progress}</div>
)}

// After response — show tool calls on the assistant message
{msg.toolCalls?.map((tc, i) => (
  <ToolResult key={i} name={tc.name} output={tc.output} details={tc.details} />
))}

Step 4 — Python tools (optional)

If the agent has Python tools (type runPythonCode in its CDF config), run the setup-python-tools skill to add Pyodide-based client-side execution:

/setup-python-tools $ARGUMENTS

That skill installs pyodide, sets up usePyodideRuntime, and wires the runtime into useAtlasChat via pythonRuntime. The library fetches Python tool code from the agent config automatically — no PythonToolConfig entries needed.

You don't need this if the agent only uses built-in or regular client tools.


Done

Start the app and you should see a streaming chat UI connected to Atlas Agent $ARGUMENTS.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/cognitedata/dune-skills/integrate-atlas-chat">View integrate-atlas-chat on skillZs</a>