Files
Benjamin Taylor 6c25273afe refactor(skills): replace nine knowledge skills with two entry points
The packaged skills had grown into a second copy of the documentation.
`runtime` and `react-core` were roughly 60% transcribed API surface, and
most of their remaining "Common Mistakes" prose already existed on a docs
page. A cached copy of an API goes stale silently: four claims in the
deleted skills contradicted the source they cited, and one of them reached
a shipped PR before it was caught.

Replace them with two skills that look the answer up instead of restating
it:

- `copilotkit` — the four search tools and two explore tools of the
  bundled `copilotkit-docs` MCP server, which corpus answers which
  question, and the instruction not to answer from memory.
- `copilotkit-cli` — the CLI, led by `copilotkit verify --json`. Since
  #1180 `verify` covers version skew, CORS, and transcription, which is
  what most of the old `copilotkit-debug` skill described by hand.

Deleted: copilotkit-setup, copilotkit-develop, copilotkit-integrations,
copilotkit-debug, copilotkit-upgrade, copilotkit-agui, copilotkit-contribute,
copilotkit-self-update, and the three package-generated skills (react-core,
runtime, a2ui-renderer).

The `skills` directory is dropped from the `files` field of the three
packages that shipped one, so the tarballs no longer carry a copy.

`public-skill-drift.test.ts` guarded wording in files that no longer exist.
It is now a link guard: every `docs.copilotkit.ai` path named by a packaged
skill has to resolve to a page in this repo, and the two entry points have
to stay free of a transcribed API surface.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-10 11:11:18 -05:00
..

CopilotKit - React Core

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Why CopilotKit?

  • Minutes to integrate - Get started quickly with our CLI
  • Framework agnostic - Works with React, Next.js, AGUI and more
  • Production-ready UI - Use customizable components or build with headless UI
  • Built-in security - Prompt injection protection
  • Open source - Full transparency and community-driven
class-support-ecosystem

🧑‍💻 Real life use cases

Deploy deeply-integrated AI assistants & agents that work alongside your users inside your applications.

headless-ui

🖥️ Code Samples

Drop in these building blocks and tailor them to your needs.

Build with Headless APIs and Pre-Built Components

// Headless UI with full control
const { visibleMessages, appendMessage, setMessages, ... } = useCopilotChat();

// Pre-built components with deep customization options (CSS + pass custom sub-components)
<CopilotPopup
  instructions={"You are assisting the user as best as you can. Answer in the best way possible given the data you have."}
  labels={{ title: "Popup Assistant", initial: "Need any help?" }}
/>
// Frontend actions + generative UI, with full streaming support
useCopilotAction({
  name: "appendToSpreadsheet",
  description: "Append rows to the current spreadsheet",
  parameters: [
    { name: "rows", type: "object[]", attributes: [{ name: "cells", type: "object[]", attributes: [{ name: "value", type: "string" }] }] }
  ],
  render: ({ status, args }) => <Spreadsheet data={canonicalSpreadsheetData(args.rows)} />,
  handler: ({ rows }) => setSpreadsheet({ ...spreadsheet, rows: [...spreadsheet.rows, ...canonicalSpreadsheetData(rows)] }),
});

Integrate In-App CoAgents with LangGraph

// Share state between app and agent
const { agentState } = useCoAgent({
  name: "basic_agent",
  initialState: { input: "NYC" }
});

// agentic generative UI
useCoAgentStateRender({
  name: "basic_agent",
  render: ({ state }) => <WeatherDisplay {...state.final_response} />,
});

// Human in the Loop (Approval)
useCopilotAction({
  name: "email_tool",
  parameters: [
    {
      name: "email_draft",
      type: "string",
      description: "The email content",
      required: true,
    },
  ],
  renderAndWaitForResponse: ({ args, status, respond }) => {
    return (
      <EmailConfirmation
        emailContent={args.email_draft || ""}
        isExecuting={status === "executing"}
        onCancel={() => respond?.({ approved: false })}
        onSend={() =>
          respond?.({
            approved: true,
            metadata: { sentAt: new Date().toISOString() },
          })
        }
      />
    );
  },
});
// intermediate agent state streaming (supports both LangGraph.js + LangGraph python)
const modifiedConfig = copilotKitCustomizeConfig(config, {
  emitIntermediateState: [
    {
      stateKey: "outline",
      tool: "set_outline",
      toolArgument: "outline",
    },
  ],
});
const response = await ChatOpenAI({ model: "gpt-4o" }).invoke(
  messages,
  modifiedConfig,
);

Documentation

To get started with CopilotKit, please check out the documentation.