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twenty/packages/twenty-docs/developers/extend/apps/logic/skills-and-agents.mdx
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martmull c2ca90c255 feat(sdk): add runAgent() to run app agents from logic functions (#21157)
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## Add `runAgent()` to the Logic Function SDK

Lets an app's logic function run one of its own AI agents server-side
and get the result back synchronously — reusing the existing agent
executor instead of a new bespoke transport.

  ### Backend
- New **`runAgent` GraphQL mutation** (metadata schema) in
`ai-agent-execution`, wrapping the existing
`AgentAsyncExecutorService.executeAgent`. Scopes the agent lookup to the
calling
  application and runs it under an application auth context.
- New `@AuthApplication()` param decorator (mirrors `@AuthWorkspace()`)
— first GraphQL resolver authenticated by an **application access
token**.
- Guarded by `WorkspaceAuthGuard` +
`SettingsPermissionGuard(PermissionFlagType.AI)`: the app's role must
grant the `AI` permission flag.

  ### SDK
- `runAgent({ agentUniversalIdentifier, prompt })` posts the mutation to
`/metadata` with the app token via a new runtime GraphQL transport.
Returns `{ result, hasNoMoreAvailableCredits
  }`.
- Refactored the connections helpers onto a shared `postAppEndpoint`
util (removes duplicated transport logic).

  ### Frontend
- App install permission modal now shows an explicit consent line —
_"Run AI agents and bill AI credits to your workspace"_ — when the app's
role requests the `AI` flag.

  ### Docs
- Documented `runAgent` and its `AI` permission-flag requirement in
_Skills & Agents_.
- Fixed outdated role-permission examples in _Roles & Permissions_
(`permissionFlags` → `permissionFlagUniversalIdentifiers`,
`PermissionFlag` → `SystemPermissionFlag`).

  ### Test plan
- [x] SDK unit tests (`run-agent.spec.ts`) — request shape, GraphQL/HTTP
error handling, missing env vars
- [x] `twenty-server`, `twenty-front`, `twenty-shared` typecheck + lint
- [ ] Manual: install an app granting the `AI` flag, call `runAgent()`
from a logic function, confirm the agent runs and credits are billed

---------

Co-authored-by: cubic-dev-ai[bot] <191113872+cubic-dev-ai[bot]@users.noreply.github.com>
2026-06-04 16:18:27 +00:00

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---
title: Skills & Agents
description: Define AI skills and agents for your app.
icon: "robot"
---
<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
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
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
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()`:
```ts src/logic-functions/run-enricher.ts
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.',
});
```
Key points:
- 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
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>
</Accordion>
</AccordionGroup>