> ## Documentation Index
> Fetch the complete documentation index at: https://twenty-claude-cool-pascal-5ay683.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Skills & Agents

> Define AI skills and agents for your app.

<Warning>
  Skills and agents are currently in alpha. The feature works but is still evolving.
</Warning>

Apps can define AI capabilities that live inside the workspace — reusable skill instructions and agents with custom system prompts.

<AccordionGroup>
  <Accordion title="defineSkill" description="Define AI agent skills">
    Skills define reusable instructions and capabilities that AI agents can use within your workspace. Use `defineSkill()` to define skills with built-in validation:

    ```ts src/skills/example-skill.ts theme={null}
    import { defineSkill } from 'twenty-sdk/define';

    export default defineSkill({
      universalIdentifier: 'a1b2c3d4-e5f6-7890-abcd-ef1234567890',
      name: 'sales-outreach',
      label: 'Sales Outreach',
      description: 'Guides the AI agent through a structured sales outreach process',
      icon: 'IconBrain',
      content: `You are a sales outreach assistant. When reaching out to a prospect:
    1. Research the company and recent news
    2. Identify the prospect's role and likely pain points
    3. Draft a personalized message referencing specific details
    4. Keep the tone professional but conversational`,
    });
    ```

    Key points:

    * `name` is a unique identifier string for the skill (kebab-case recommended).
    * `label` is the human-readable display name shown in the UI.
    * `content` contains the skill instructions — this is the text the AI agent uses.
    * `icon` (optional) sets the icon displayed in the UI.
    * `description` (optional) provides additional context about the skill's purpose.
  </Accordion>

  <Accordion title="defineAgent" description="Define AI agents with custom prompts">
    Agents are AI assistants that live inside your workspace. Use `defineAgent()` to create agents with a custom system prompt:

    ```ts src/agents/example-agent.ts theme={null}
    import { defineAgent } from 'twenty-sdk/define';

    export default defineAgent({
      universalIdentifier: 'b3c4d5e6-f7a8-9012-bcde-f34567890123',
      name: 'sales-assistant',
      label: 'Sales Assistant',
      description: 'Helps the sales team draft outreach emails and research prospects',
      icon: 'IconRobot',
      prompt: 'You are a helpful sales assistant. Help users with their questions and tasks.',
    });
    ```

    Key points:

    * `name` is the unique identifier string for the agent (kebab-case recommended).
    * `label` is the display name shown in the UI.
    * `prompt` is the system prompt that defines the agent's behavior.
    * `description` (optional) provides context about what the agent does.
    * `icon` (optional) sets the icon displayed in the UI.
    * `modelId` (optional) overrides the default AI model used by the agent.
    * `responseFormat` (optional) controls the shape of the agent's output. Defaults to `{ type: 'text' }` for free-form text. Use `{ type: 'json', schema }` to force structured JSON output.

    By default an agent returns free-form text. To get structured output, set `responseFormat` to `{ type: 'json' }` and provide a `schema`:

    ```ts src/agents/structured-agent.ts theme={null}
    import { defineAgent } from 'twenty-sdk/define';

    export default defineAgent({
      universalIdentifier: 'c4d5e6f7-a8b9-0123-cdef-456789012345',
      name: 'lead-scorer',
      label: 'Lead Scorer',
      prompt: 'Score the lead and explain your reasoning.',
      responseFormat: {
        type: 'json',
        schema: {
          type: 'object',
          properties: {
            score: { type: 'number', description: 'Lead score from 0 to 100' },
            summary: { type: 'string', description: 'Short reasoning for the score' },
          },
          required: ['score', 'summary'],
          additionalProperties: false,
        },
      },
    });
    ```

    Schema notes:

    * The schema is a flat object: each property's `type` must be a primitive (`string`, `number`, or `boolean`). Nested objects and arrays are not supported.
    * `description` (optional) on each property guides the model on what to put there.
    * `required` (optional) lists the properties the model must always return.
    * `additionalProperties: false` (optional) forbids any property not declared in `properties`.
  </Accordion>

  <Accordion title="runAgent" description="Run an agent from a logic function">
    `runAgent()` lets a logic function run one of your app's agents (with its
    skills and tools). Identify the agent by the `universalIdentifier` you passed
    to `defineAgent()`. Pass either a `prompt` string or a `messages` conversation
    history — not both:

    ```ts src/logic-functions/run-enricher.ts theme={null}
    import { runAgent } from 'twenty-sdk/logic-function';

    const { result, error, success } = await runAgent({
      agentUniversalIdentifier: 'b3c4d5e6-f7a8-9012-bcde-f34567890123',
      prompt: 'Enrich House Ad <recordId>: fill empty fields from its listing URL.',
    });
    ```

    For multi-turn bots (Slack, Discord, Teams, …), pass thread history as
    `messages` instead of a single `prompt`:

    ```ts src/logic-functions/reply-in-thread.ts theme={null}
    import { runAgent } from 'twenty-sdk/logic-function';

    const { result, error, success } = await runAgent({
      agentUniversalIdentifier: 'b3c4d5e6-f7a8-9012-bcde-f34567890123',
      messages: [
        { role: 'user', content: 'Who owns Acme?' },
        { role: 'assistant', content: 'Sarah owns the Acme account.' },
        { role: 'user', content: 'What was the last touchpoint?' },
      ],
    });
    ```

    Key points:

    * Provide **exactly one** of `prompt` (string) or `messages` (1 to 100 entries
      of `{ role: 'user' | 'assistant', content: string }`).
    * The agent runs **synchronously** and can read/update records itself via its
      own tools — `runAgent()` resolves once the run completes.
    * An app can only run its own agents.
    * The app's [default role](/developers/extend/apps/config/roles) must grant the
      `AI` permission flag — add `SystemPermissionFlag.AI` to its
      `permissionFlagUniversalIdentifiers` (or set `canAccessAllTools: true`).
      Without it, `runAgent()` fails with a permission error.
    * Set a generous `timeoutSeconds` on the logic function — agent runs can take
      several seconds.
    * `success` is `true` and `result` is non-null when the run completes; on
      failure `success` is `false`, `result` is `null`, and `error` holds the
      reason (for example, when the workspace ran out of AI credits mid-run).

    ```ts src/roles/default-role.ts theme={null}
    import { defineApplicationRole, SystemPermissionFlag } from 'twenty-sdk/define';

    export default defineApplicationRole({
      universalIdentifier: 'b648f87b-1d26-4961-b974-0908fd991061',
      label: 'Default function role',
      // runAgent() requires the AI permission flag on the app's default role.
      permissionFlagUniversalIdentifiers: [SystemPermissionFlag.AI],
    });
    ```

    <Warning>
      **Avoid loops:** if you call `runAgent()` from a `*.updated` database-event
      trigger and the agent updates the same record, scope the trigger with
      `updatedFields` to a field the agent never writes (e.g. the source URL), or
      guard on whether any target field is still empty before calling `runAgent()`.
    </Warning>

    ### Running on behalf of a workspace member

    Pass `runAsWorkspaceMemberId` when the run is triggered by a person — a chat
    bot answering a message, for instance — so the agent acts as that member
    instead of as the app:

    ```ts src/logic-functions/answer-question.ts theme={null}
    const { result } = await runAgent({
      agentUniversalIdentifier: 'b3c4d5e6-f7a8-9012-bcde-f34567890123',
      prompt: 'How many open opportunities do we have?',
      runAsWorkspaceMemberId: '20202020-0687-4c41-b707-ed1bfca972a7',
    });
    ```

    The run then acts with the **member's own role**: it can do whatever that
    member can do and nothing more, records it creates are attributed to them, and
    their row-level permissions apply. The agent's role does not participate — it
    is the app's default for runs with nobody behind them. Omit the field for
    autonomous runs (scheduled jobs, database-event triggers): those keep the
    agent's own role. The acting application stays attached to the run's context
    for provenance, without narrowing the member's permissions.

    Your app is responsible for mapping the person who triggered the run to a
    workspace member. Naming one requires an app access token, and what a token may
    name depends on whether it carries a user:

    * A token with **no user attached** may name any member. A logic function runs
      with one, and so do tokens minted through `client_credentials` or from an API
      key.
    * A token issued **on behalf of a user**, as a front component receives, may
      only name that user's own member.

    Anything else — a plain user session, an API key without an app token — may not
    name a member at all.

    <Warning>
      `runAgent()` throws when the workspace member cannot be resolved — an
      unknown or removed member, or one with no role. It never falls back to the
      agent's own role, since that would grant more access than the caller asked
      for.
    </Warning>
  </Accordion>
</AccordionGroup>